diff --git a/gcdata/mcppareto.png b/gcdata/mcppareto.png
index 1fba32b..c02c8d0 100644
Binary files a/gcdata/mcppareto.png and b/gcdata/mcppareto.png differ
diff --git a/gcdata/mctest.ipynb b/gcdata/mctest.ipynb
index 3ec7581..36c7cf3 100644
--- a/gcdata/mctest.ipynb
+++ b/gcdata/mctest.ipynb
@@ -108,278 +108,278 @@
       "测试实例: DSJC0500.5.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.0531秒, 使用颜色数:68\n",
+      "执行时间:0.0579秒, 使用颜色数:68\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:17.5173秒, 使用颜色数:65\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.2342秒, 使用颜色数:65\n",
+      "执行时间:18.2027秒, 使用颜色数:65\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:0.0772秒, 使用颜色数:72\n",
+      "执行时间:0.0938秒, 使用颜色数:72\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.0384秒, 使用颜色数:72\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.2781秒, 使用颜色数:65\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0417秒, 使用颜色数:72\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.0647秒, 使用颜色数:71\n",
+      "执行时间:0.0708秒, 使用颜色数:71\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:12.9052秒, 使用颜色数:65\n",
+      "执行时间:13.6344秒, 使用颜色数:65\n",
       "\n",
       "测试实例: DSJC1000.9.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.1921秒, 使用颜色数:316\n",
+      "执行时间:0.2167秒, 使用颜色数:316\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:141.4497秒, 使用颜色数:299\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.7749秒, 使用颜色数:299\n",
+      "执行时间:122.6014秒, 使用颜色数:299\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:1.1940秒, 使用颜色数:321\n",
+      "执行时间:1.1258秒, 使用颜色数:321\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.1230秒, 使用颜色数:321\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.6846秒, 使用颜色数:299\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0872秒, 使用颜色数:321\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.5992秒, 使用颜色数:313\n",
+      "执行时间:0.4910秒, 使用颜色数:313\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:62.9649秒, 使用颜色数:299\n",
+      "执行时间:61.6497秒, 使用颜色数:299\n",
       "\n",
       "测试实例: DSJC0500.1.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.0273秒, 使用颜色数:18\n",
+      "执行时间:0.0271秒, 使用颜色数:18\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:9.1615秒, 使用颜色数:16\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.0434秒, 使用颜色数:16\n",
+      "执行时间:8.2985秒, 使用颜色数:16\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:0.0063秒, 使用颜色数:20\n",
+      "执行时间:0.0060秒, 使用颜色数:20\n",
       "\n",
-      "使用算法: 贪心\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.0395秒, 使用颜色数:16\n",
+      "\n",
+      "使用算法: Greedy\n",
       "执行时间:0.0208秒, 使用颜色数:20\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.0190秒, 使用颜色数:18\n",
+      "执行时间:0.0193秒, 使用颜色数:18\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:8.4256秒, 使用颜色数:16\n",
+      "执行时间:7.5141秒, 使用颜色数:16\n",
       "\n",
       "测试实例: DSJC0250.1.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.0108秒, 使用颜色数:12\n",
+      "执行时间:0.0059秒, 使用颜色数:12\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:1.9122秒, 使用颜色数:10\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.0242秒, 使用颜色数:10\n",
+      "执行时间:0.9747秒, 使用颜色数:10\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:0.0047秒, 使用颜色数:13\n",
+      "执行时间:0.0015秒, 使用颜色数:13\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.0098秒, 使用颜色数:13\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.0082秒, 使用颜色数:10\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0048秒, 使用颜色数:13\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.0086秒, 使用颜色数:11\n",
+      "执行时间:0.0041秒, 使用颜色数:11\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:1.6975秒, 使用颜色数:10\n",
+      "执行时间:0.8288秒, 使用颜色数:10\n",
       "\n",
       "测试实例: DSJC0125.9.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.0037秒, 使用颜色数:53\n",
+      "执行时间:0.0018秒, 使用颜色数:53\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:0.3753秒, 使用颜色数:51\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.0160秒, 使用颜色数:51\n",
+      "执行时间:0.1796秒, 使用颜色数:51\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:0.0116秒, 使用颜色数:56\n",
+      "执行时间:0.0047秒, 使用颜色数:56\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.0023秒, 使用颜色数:56\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.0083秒, 使用颜色数:51\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0015秒, 使用颜色数:56\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.0068秒, 使用颜色数:53\n",
+      "执行时间:0.0027秒, 使用颜色数:53\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:0.2167秒, 使用颜色数:51\n",
+      "执行时间:0.1214秒, 使用颜色数:51\n",
       "\n",
       "测试实例: DSJC0250.5.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.0111秒, 使用颜色数:40\n",
+      "执行时间:0.0062秒, 使用颜色数:40\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:2.3817秒, 使用颜色数:37\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.0539秒, 使用颜色数:37\n",
+      "执行时间:1.2001秒, 使用颜色数:37\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:0.0163秒, 使用颜色数:43\n",
+      "执行时间:0.0080秒, 使用颜色数:43\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.0107秒, 使用颜色数:43\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.0207秒, 使用颜色数:37\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0052秒, 使用颜色数:43\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.0159秒, 使用颜色数:41\n",
+      "执行时间:0.0065秒, 使用颜色数:41\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:1.7535秒, 使用颜色数:37\n",
+      "执行时间:0.9142秒, 使用颜色数:37\n",
       "\n",
       "测试实例: DSJC0125.5.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.0037秒, 使用颜色数:24\n",
+      "执行时间:0.0016秒, 使用颜色数:24\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:0.3252秒, 使用颜色数:22\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.0094秒, 使用颜色数:22\n",
+      "执行时间:0.1555秒, 使用颜色数:22\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:0.0037秒, 使用颜色数:26\n",
+      "执行时间:0.0018秒, 使用颜色数:26\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.0022秒, 使用颜色数:26\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.0051秒, 使用颜色数:22\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0014秒, 使用颜色数:26\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.0035秒, 使用颜色数:23\n",
+      "执行时间:0.0013秒, 使用颜色数:23\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:0.2311秒, 使用颜色数:22\n",
+      "执行时间:0.1308秒, 使用颜色数:22\n",
       "\n",
       "测试实例: DSJC0250.9.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.0138秒, 使用颜色数:92\n",
+      "执行时间:0.0065秒, 使用颜色数:92\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:2.7876秒, 使用颜色数:92\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.0882秒, 使用颜色数:92\n",
+      "执行时间:1.4176秒, 使用颜色数:92\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:0.0623秒, 使用颜色数:99\n",
+      "执行时间:0.0281秒, 使用颜色数:99\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.0098秒, 使用颜色数:99\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.0361秒, 使用颜色数:92\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0054秒, 使用颜色数:99\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.0273秒, 使用颜色数:93\n",
+      "执行时间:0.0130秒, 使用颜色数:93\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:1.9282秒, 使用颜色数:92\n",
+      "执行时间:0.9777秒, 使用颜色数:92\n",
       "\n",
       "测试实例: DSJC0125.1.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.0032秒, 使用颜色数:7\n",
+      "执行时间:0.0016秒, 使用颜色数:7\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:0.2459秒, 使用颜色数:6\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.0061秒, 使用颜色数:6\n",
+      "执行时间:0.2009秒, 使用颜色数:6\n",
       "\n",
       "使用算法: MEoH-MCP\n",
       "执行时间:0.0006秒, 使用颜色数:8\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.0022秒, 使用颜色数:8\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.0059秒, 使用颜色数:6\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0028秒, 使用颜色数:8\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.0017秒, 使用颜色数:7\n",
+      "执行时间:0.0022秒, 使用颜色数:7\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:0.2033秒, 使用颜色数:6\n",
+      "执行时间:0.2098秒, 使用颜色数:6\n",
       "\n",
       "测试实例: DSJC1000.1.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.1838秒, 使用颜色数:29\n",
+      "执行时间:0.1945秒, 使用颜色数:29\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:80.1908秒, 使用颜色数:27\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.1365秒, 使用颜色数:27\n",
+      "执行时间:67.5939秒, 使用颜色数:27\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:0.0256秒, 使用颜色数:31\n",
+      "执行时间:0.0318秒, 使用颜色数:31\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.0782秒, 使用颜色数:31\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.1373秒, 使用颜色数:27\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0780秒, 使用颜色数:31\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.0820秒, 使用颜色数:29\n",
+      "执行时间:0.0838秒, 使用颜色数:29\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:67.1028秒, 使用颜色数:27\n",
+      "执行时间:57.1171秒, 使用颜色数:27\n",
       "\n",
       "测试实例: DSJC0500.9.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.0550秒, 使用颜色数:171\n",
+      "执行时间:0.0266秒, 使用颜色数:171\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:21.5202秒, 使用颜色数:170\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.1652秒, 使用颜色数:170\n",
+      "执行时间:11.5300秒, 使用颜色数:170\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:0.2121秒, 使用颜色数:175\n",
+      "执行时间:0.1568秒, 使用颜色数:175\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.0248秒, 使用颜色数:175\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.1534秒, 使用颜色数:170\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0220秒, 使用颜色数:175\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.0891秒, 使用颜色数:169\n",
+      "执行时间:0.0806秒, 使用颜色数:169\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:9.3176秒, 使用颜色数:170\n",
+      "执行时间:7.5806秒, 使用颜色数:170\n",
       "\n",
       "测试实例: DSJC1000.5.txt\n",
       "\n",
       "使用算法: FunSearch-MCP\n",
-      "执行时间:0.1247秒, 使用颜色数:123\n",
+      "执行时间:0.1027秒, 使用颜色数:123\n",
       "\n",
       "使用算法: EoH-MCP\n",
-      "执行时间:122.0818秒, 使用颜色数:115\n",
-      "\n",
-      "使用算法: AAE-MCP\n",
-      "执行时间:0.9329秒, 使用颜色数:115\n",
+      "执行时间:86.2889秒, 使用颜色数:115\n",
       "\n",
       "使用算法: MEoH-MCP\n",
-      "执行时间:0.4898秒, 使用颜色数:127\n",
+      "执行时间:0.2535秒, 使用颜色数:127\n",
       "\n",
-      "使用算法: 贪心\n",
-      "执行时间:0.1717秒, 使用颜色数:127\n",
+      "使用算法: AAE-MCP\n",
+      "执行时间:0.3925秒, 使用颜色数:115\n",
+      "\n",
+      "使用算法: Greedy\n",
+      "执行时间:0.0824秒, 使用颜色数:127\n",
       "\n",
       "使用算法: Welsh-Powell\n",
-      "执行时间:0.3686秒, 使用颜色数:121\n",
+      "执行时间:0.1860秒, 使用颜色数:121\n",
       "\n",
       "使用算法: DSATUR\n",
-      "执行时间:69.0443秒, 使用颜色数:115\n",
+      "执行时间:62.1337秒, 使用颜色数:115\n",
       "\n",
       "所有算法在各个实例上的表现:\n",
       "\n",
@@ -396,13 +396,13 @@
       "  DSJC1000.1.txt: 使用颜色数 = 29\n",
       "  DSJC0500.9.txt: 使用颜色数 = 171\n",
       "  DSJC1000.5.txt: 使用颜色数 = 123\n",
-      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.053112030029296875, 'DSJC1000.9.txt': 0.19205880165100098, 'DSJC0500.1.txt': 0.027337312698364258, 'DSJC0250.1.txt': 0.01080775260925293, 'DSJC0125.9.txt': 0.0036962032318115234, 'DSJC0250.5.txt': 0.011050939559936523, 'DSJC0125.5.txt': 0.0036878585815429688, 'DSJC0250.9.txt': 0.013804912567138672, 'DSJC0125.1.txt': 0.0032007694244384766, 'DSJC1000.1.txt': 0.18375301361083984, 'DSJC0500.9.txt': 0.05500006675720215, 'DSJC1000.5.txt': 0.1247410774230957}\n",
-      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 17.517324686050415, 'DSJC1000.9.txt': 141.44973587989807, 'DSJC0500.1.txt': 9.161540746688843, 'DSJC0250.1.txt': 1.9121909141540527, 'DSJC0125.9.txt': 0.3752713203430176, 'DSJC0250.5.txt': 2.381682872772217, 'DSJC0125.5.txt': 0.3251969814300537, 'DSJC0250.9.txt': 2.7875781059265137, 'DSJC0125.1.txt': 0.2459268569946289, 'DSJC1000.1.txt': 80.19077229499817, 'DSJC0500.9.txt': 21.52015209197998, 'DSJC1000.5.txt': 122.0817620754242}\n",
-      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.23422980308532715, 'DSJC1000.9.txt': 0.7749209403991699, 'DSJC0500.1.txt': 0.04343390464782715, 'DSJC0250.1.txt': 0.024243831634521484, 'DSJC0125.9.txt': 0.015971660614013672, 'DSJC0250.5.txt': 0.05388021469116211, 'DSJC0125.5.txt': 0.009436845779418945, 'DSJC0250.9.txt': 0.0881800651550293, 'DSJC0125.1.txt': 0.006103992462158203, 'DSJC1000.1.txt': 0.13647675514221191, 'DSJC0500.9.txt': 0.16518092155456543, 'DSJC1000.5.txt': 0.9329369068145752}\n",
-      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.07716202735900879, 'DSJC1000.9.txt': 1.1940302848815918, 'DSJC0500.1.txt': 0.006262063980102539, 'DSJC0250.1.txt': 0.004677772521972656, 'DSJC0125.9.txt': 0.011601924896240234, 'DSJC0250.5.txt': 0.016296863555908203, 'DSJC0125.5.txt': 0.0036668777465820312, 'DSJC0250.9.txt': 0.062290191650390625, 'DSJC0125.1.txt': 0.0006039142608642578, 'DSJC1000.1.txt': 0.02557992935180664, 'DSJC0500.9.txt': 0.21206116676330566, 'DSJC1000.5.txt': 0.48981499671936035}\n",
-      "  贪心: 执行时间 = {'DSJC0500.5.txt': 0.0383601188659668, 'DSJC1000.9.txt': 0.12301898002624512, 'DSJC0500.1.txt': 0.020846843719482422, 'DSJC0250.1.txt': 0.009821891784667969, 'DSJC0125.9.txt': 0.002260923385620117, 'DSJC0250.5.txt': 0.010657072067260742, 'DSJC0125.5.txt': 0.0022068023681640625, 'DSJC0250.9.txt': 0.009806156158447266, 'DSJC0125.1.txt': 0.0021581649780273438, 'DSJC1000.1.txt': 0.07824492454528809, 'DSJC0500.9.txt': 0.024803876876831055, 'DSJC1000.5.txt': 0.17168307304382324}\n",
-      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.06465888023376465, 'DSJC1000.9.txt': 0.5991549491882324, 'DSJC0500.1.txt': 0.018989086151123047, 'DSJC0250.1.txt': 0.008564233779907227, 'DSJC0125.9.txt': 0.006818056106567383, 'DSJC0250.5.txt': 0.015928030014038086, 'DSJC0125.5.txt': 0.0034928321838378906, 'DSJC0250.9.txt': 0.027268171310424805, 'DSJC0125.1.txt': 0.0017459392547607422, 'DSJC1000.1.txt': 0.08201384544372559, 'DSJC0500.9.txt': 0.0891120433807373, 'DSJC1000.5.txt': 0.36855101585388184}\n",
-      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 12.905187129974365, 'DSJC1000.9.txt': 62.964935064315796, 'DSJC0500.1.txt': 8.425614833831787, 'DSJC0250.1.txt': 1.6975018978118896, 'DSJC0125.9.txt': 0.216688871383667, 'DSJC0250.5.txt': 1.7534830570220947, 'DSJC0125.5.txt': 0.2310791015625, 'DSJC0250.9.txt': 1.9282159805297852, 'DSJC0125.1.txt': 0.20327496528625488, 'DSJC1000.1.txt': 67.10282707214355, 'DSJC0500.9.txt': 9.31760311126709, 'DSJC1000.5.txt': 69.04426693916321}\n",
+      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.057862043380737305, 'DSJC1000.9.txt': 0.21670818328857422, 'DSJC0500.1.txt': 0.027055978775024414, 'DSJC0250.1.txt': 0.005907773971557617, 'DSJC0125.9.txt': 0.0018310546875, 'DSJC0250.5.txt': 0.006178855895996094, 'DSJC0125.5.txt': 0.0016169548034667969, 'DSJC0250.9.txt': 0.006543159484863281, 'DSJC0125.1.txt': 0.0015578269958496094, 'DSJC1000.1.txt': 0.19445085525512695, 'DSJC0500.9.txt': 0.026648759841918945, 'DSJC1000.5.txt': 0.10271525382995605}\n",
+      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 18.20269513130188, 'DSJC1000.9.txt': 122.60140109062195, 'DSJC0500.1.txt': 8.298484086990356, 'DSJC0250.1.txt': 0.9747259616851807, 'DSJC0125.9.txt': 0.17962121963500977, 'DSJC0250.5.txt': 1.2000939846038818, 'DSJC0125.5.txt': 0.15546917915344238, 'DSJC0250.9.txt': 1.4175689220428467, 'DSJC0125.1.txt': 0.2008528709411621, 'DSJC1000.1.txt': 67.5939428806305, 'DSJC0500.9.txt': 11.530013084411621, 'DSJC1000.5.txt': 86.28894186019897}\n",
+      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.09375882148742676, 'DSJC1000.9.txt': 1.1257750988006592, 'DSJC0500.1.txt': 0.005967140197753906, 'DSJC0250.1.txt': 0.0014951229095458984, 'DSJC0125.9.txt': 0.0046842098236083984, 'DSJC0250.5.txt': 0.008018016815185547, 'DSJC0125.5.txt': 0.0017600059509277344, 'DSJC0250.9.txt': 0.02807331085205078, 'DSJC0125.1.txt': 0.0006096363067626953, 'DSJC1000.1.txt': 0.03177499771118164, 'DSJC0500.9.txt': 0.15678906440734863, 'DSJC1000.5.txt': 0.25353002548217773}\n",
+      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.27809929847717285, 'DSJC1000.9.txt': 0.6846380233764648, 'DSJC0500.1.txt': 0.03948807716369629, 'DSJC0250.1.txt': 0.008155107498168945, 'DSJC0125.9.txt': 0.008310079574584961, 'DSJC0250.5.txt': 0.02069091796875, 'DSJC0125.5.txt': 0.005082130432128906, 'DSJC0250.9.txt': 0.03608989715576172, 'DSJC0125.1.txt': 0.005899906158447266, 'DSJC1000.1.txt': 0.13730883598327637, 'DSJC0500.9.txt': 0.1533823013305664, 'DSJC1000.5.txt': 0.3924710750579834}\n",
+      "  Greedy: 执行时间 = {'DSJC0500.5.txt': 0.04168081283569336, 'DSJC1000.9.txt': 0.08718514442443848, 'DSJC0500.1.txt': 0.02080392837524414, 'DSJC0250.1.txt': 0.004765987396240234, 'DSJC0125.9.txt': 0.0015120506286621094, 'DSJC0250.5.txt': 0.005215167999267578, 'DSJC0125.5.txt': 0.0014150142669677734, 'DSJC0250.9.txt': 0.005381107330322266, 'DSJC0125.1.txt': 0.0027589797973632812, 'DSJC1000.1.txt': 0.07802486419677734, 'DSJC0500.9.txt': 0.02198195457458496, 'DSJC1000.5.txt': 0.08238601684570312}\n",
+      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.0707998275756836, 'DSJC1000.9.txt': 0.491008996963501, 'DSJC0500.1.txt': 0.01932525634765625, 'DSJC0250.1.txt': 0.004117012023925781, 'DSJC0125.9.txt': 0.002706766128540039, 'DSJC0250.5.txt': 0.0064661502838134766, 'DSJC0125.5.txt': 0.0013499259948730469, 'DSJC0250.9.txt': 0.013007879257202148, 'DSJC0125.1.txt': 0.002179861068725586, 'DSJC1000.1.txt': 0.0838019847869873, 'DSJC0500.9.txt': 0.08063507080078125, 'DSJC1000.5.txt': 0.18603014945983887}\n",
+      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 13.63444995880127, 'DSJC1000.9.txt': 61.64974927902222, 'DSJC0500.1.txt': 7.514086961746216, 'DSJC0250.1.txt': 0.8288030624389648, 'DSJC0125.9.txt': 0.12142586708068848, 'DSJC0250.5.txt': 0.9142141342163086, 'DSJC0125.5.txt': 0.13076090812683105, 'DSJC0250.9.txt': 0.9776561260223389, 'DSJC0125.1.txt': 0.20984697341918945, 'DSJC1000.1.txt': 57.11710214614868, 'DSJC0500.9.txt': 7.5806498527526855, 'DSJC1000.5.txt': 62.13368821144104}\n",
       "\n",
       "EoH-MCP:\n",
       "  DSJC0500.5.txt: 使用颜色数 = 65\n",
@@ -417,34 +417,13 @@
       "  DSJC1000.1.txt: 使用颜色数 = 27\n",
       "  DSJC0500.9.txt: 使用颜色数 = 170\n",
       "  DSJC1000.5.txt: 使用颜色数 = 115\n",
-      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.053112030029296875, 'DSJC1000.9.txt': 0.19205880165100098, 'DSJC0500.1.txt': 0.027337312698364258, 'DSJC0250.1.txt': 0.01080775260925293, 'DSJC0125.9.txt': 0.0036962032318115234, 'DSJC0250.5.txt': 0.011050939559936523, 'DSJC0125.5.txt': 0.0036878585815429688, 'DSJC0250.9.txt': 0.013804912567138672, 'DSJC0125.1.txt': 0.0032007694244384766, 'DSJC1000.1.txt': 0.18375301361083984, 'DSJC0500.9.txt': 0.05500006675720215, 'DSJC1000.5.txt': 0.1247410774230957}\n",
-      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 17.517324686050415, 'DSJC1000.9.txt': 141.44973587989807, 'DSJC0500.1.txt': 9.161540746688843, 'DSJC0250.1.txt': 1.9121909141540527, 'DSJC0125.9.txt': 0.3752713203430176, 'DSJC0250.5.txt': 2.381682872772217, 'DSJC0125.5.txt': 0.3251969814300537, 'DSJC0250.9.txt': 2.7875781059265137, 'DSJC0125.1.txt': 0.2459268569946289, 'DSJC1000.1.txt': 80.19077229499817, 'DSJC0500.9.txt': 21.52015209197998, 'DSJC1000.5.txt': 122.0817620754242}\n",
-      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.23422980308532715, 'DSJC1000.9.txt': 0.7749209403991699, 'DSJC0500.1.txt': 0.04343390464782715, 'DSJC0250.1.txt': 0.024243831634521484, 'DSJC0125.9.txt': 0.015971660614013672, 'DSJC0250.5.txt': 0.05388021469116211, 'DSJC0125.5.txt': 0.009436845779418945, 'DSJC0250.9.txt': 0.0881800651550293, 'DSJC0125.1.txt': 0.006103992462158203, 'DSJC1000.1.txt': 0.13647675514221191, 'DSJC0500.9.txt': 0.16518092155456543, 'DSJC1000.5.txt': 0.9329369068145752}\n",
-      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.07716202735900879, 'DSJC1000.9.txt': 1.1940302848815918, 'DSJC0500.1.txt': 0.006262063980102539, 'DSJC0250.1.txt': 0.004677772521972656, 'DSJC0125.9.txt': 0.011601924896240234, 'DSJC0250.5.txt': 0.016296863555908203, 'DSJC0125.5.txt': 0.0036668777465820312, 'DSJC0250.9.txt': 0.062290191650390625, 'DSJC0125.1.txt': 0.0006039142608642578, 'DSJC1000.1.txt': 0.02557992935180664, 'DSJC0500.9.txt': 0.21206116676330566, 'DSJC1000.5.txt': 0.48981499671936035}\n",
-      "  贪心: 执行时间 = {'DSJC0500.5.txt': 0.0383601188659668, 'DSJC1000.9.txt': 0.12301898002624512, 'DSJC0500.1.txt': 0.020846843719482422, 'DSJC0250.1.txt': 0.009821891784667969, 'DSJC0125.9.txt': 0.002260923385620117, 'DSJC0250.5.txt': 0.010657072067260742, 'DSJC0125.5.txt': 0.0022068023681640625, 'DSJC0250.9.txt': 0.009806156158447266, 'DSJC0125.1.txt': 0.0021581649780273438, 'DSJC1000.1.txt': 0.07824492454528809, 'DSJC0500.9.txt': 0.024803876876831055, 'DSJC1000.5.txt': 0.17168307304382324}\n",
-      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.06465888023376465, 'DSJC1000.9.txt': 0.5991549491882324, 'DSJC0500.1.txt': 0.018989086151123047, 'DSJC0250.1.txt': 0.008564233779907227, 'DSJC0125.9.txt': 0.006818056106567383, 'DSJC0250.5.txt': 0.015928030014038086, 'DSJC0125.5.txt': 0.0034928321838378906, 'DSJC0250.9.txt': 0.027268171310424805, 'DSJC0125.1.txt': 0.0017459392547607422, 'DSJC1000.1.txt': 0.08201384544372559, 'DSJC0500.9.txt': 0.0891120433807373, 'DSJC1000.5.txt': 0.36855101585388184}\n",
-      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 12.905187129974365, 'DSJC1000.9.txt': 62.964935064315796, 'DSJC0500.1.txt': 8.425614833831787, 'DSJC0250.1.txt': 1.6975018978118896, 'DSJC0125.9.txt': 0.216688871383667, 'DSJC0250.5.txt': 1.7534830570220947, 'DSJC0125.5.txt': 0.2310791015625, 'DSJC0250.9.txt': 1.9282159805297852, 'DSJC0125.1.txt': 0.20327496528625488, 'DSJC1000.1.txt': 67.10282707214355, 'DSJC0500.9.txt': 9.31760311126709, 'DSJC1000.5.txt': 69.04426693916321}\n",
-      "\n",
-      "AAE-MCP:\n",
-      "  DSJC0500.5.txt: 使用颜色数 = 65\n",
-      "  DSJC1000.9.txt: 使用颜色数 = 299\n",
-      "  DSJC0500.1.txt: 使用颜色数 = 16\n",
-      "  DSJC0250.1.txt: 使用颜色数 = 10\n",
-      "  DSJC0125.9.txt: 使用颜色数 = 51\n",
-      "  DSJC0250.5.txt: 使用颜色数 = 37\n",
-      "  DSJC0125.5.txt: 使用颜色数 = 22\n",
-      "  DSJC0250.9.txt: 使用颜色数 = 92\n",
-      "  DSJC0125.1.txt: 使用颜色数 = 6\n",
-      "  DSJC1000.1.txt: 使用颜色数 = 27\n",
-      "  DSJC0500.9.txt: 使用颜色数 = 170\n",
-      "  DSJC1000.5.txt: 使用颜色数 = 115\n",
-      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.053112030029296875, 'DSJC1000.9.txt': 0.19205880165100098, 'DSJC0500.1.txt': 0.027337312698364258, 'DSJC0250.1.txt': 0.01080775260925293, 'DSJC0125.9.txt': 0.0036962032318115234, 'DSJC0250.5.txt': 0.011050939559936523, 'DSJC0125.5.txt': 0.0036878585815429688, 'DSJC0250.9.txt': 0.013804912567138672, 'DSJC0125.1.txt': 0.0032007694244384766, 'DSJC1000.1.txt': 0.18375301361083984, 'DSJC0500.9.txt': 0.05500006675720215, 'DSJC1000.5.txt': 0.1247410774230957}\n",
-      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 17.517324686050415, 'DSJC1000.9.txt': 141.44973587989807, 'DSJC0500.1.txt': 9.161540746688843, 'DSJC0250.1.txt': 1.9121909141540527, 'DSJC0125.9.txt': 0.3752713203430176, 'DSJC0250.5.txt': 2.381682872772217, 'DSJC0125.5.txt': 0.3251969814300537, 'DSJC0250.9.txt': 2.7875781059265137, 'DSJC0125.1.txt': 0.2459268569946289, 'DSJC1000.1.txt': 80.19077229499817, 'DSJC0500.9.txt': 21.52015209197998, 'DSJC1000.5.txt': 122.0817620754242}\n",
-      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.23422980308532715, 'DSJC1000.9.txt': 0.7749209403991699, 'DSJC0500.1.txt': 0.04343390464782715, 'DSJC0250.1.txt': 0.024243831634521484, 'DSJC0125.9.txt': 0.015971660614013672, 'DSJC0250.5.txt': 0.05388021469116211, 'DSJC0125.5.txt': 0.009436845779418945, 'DSJC0250.9.txt': 0.0881800651550293, 'DSJC0125.1.txt': 0.006103992462158203, 'DSJC1000.1.txt': 0.13647675514221191, 'DSJC0500.9.txt': 0.16518092155456543, 'DSJC1000.5.txt': 0.9329369068145752}\n",
-      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.07716202735900879, 'DSJC1000.9.txt': 1.1940302848815918, 'DSJC0500.1.txt': 0.006262063980102539, 'DSJC0250.1.txt': 0.004677772521972656, 'DSJC0125.9.txt': 0.011601924896240234, 'DSJC0250.5.txt': 0.016296863555908203, 'DSJC0125.5.txt': 0.0036668777465820312, 'DSJC0250.9.txt': 0.062290191650390625, 'DSJC0125.1.txt': 0.0006039142608642578, 'DSJC1000.1.txt': 0.02557992935180664, 'DSJC0500.9.txt': 0.21206116676330566, 'DSJC1000.5.txt': 0.48981499671936035}\n",
-      "  贪心: 执行时间 = {'DSJC0500.5.txt': 0.0383601188659668, 'DSJC1000.9.txt': 0.12301898002624512, 'DSJC0500.1.txt': 0.020846843719482422, 'DSJC0250.1.txt': 0.009821891784667969, 'DSJC0125.9.txt': 0.002260923385620117, 'DSJC0250.5.txt': 0.010657072067260742, 'DSJC0125.5.txt': 0.0022068023681640625, 'DSJC0250.9.txt': 0.009806156158447266, 'DSJC0125.1.txt': 0.0021581649780273438, 'DSJC1000.1.txt': 0.07824492454528809, 'DSJC0500.9.txt': 0.024803876876831055, 'DSJC1000.5.txt': 0.17168307304382324}\n",
-      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.06465888023376465, 'DSJC1000.9.txt': 0.5991549491882324, 'DSJC0500.1.txt': 0.018989086151123047, 'DSJC0250.1.txt': 0.008564233779907227, 'DSJC0125.9.txt': 0.006818056106567383, 'DSJC0250.5.txt': 0.015928030014038086, 'DSJC0125.5.txt': 0.0034928321838378906, 'DSJC0250.9.txt': 0.027268171310424805, 'DSJC0125.1.txt': 0.0017459392547607422, 'DSJC1000.1.txt': 0.08201384544372559, 'DSJC0500.9.txt': 0.0891120433807373, 'DSJC1000.5.txt': 0.36855101585388184}\n",
-      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 12.905187129974365, 'DSJC1000.9.txt': 62.964935064315796, 'DSJC0500.1.txt': 8.425614833831787, 'DSJC0250.1.txt': 1.6975018978118896, 'DSJC0125.9.txt': 0.216688871383667, 'DSJC0250.5.txt': 1.7534830570220947, 'DSJC0125.5.txt': 0.2310791015625, 'DSJC0250.9.txt': 1.9282159805297852, 'DSJC0125.1.txt': 0.20327496528625488, 'DSJC1000.1.txt': 67.10282707214355, 'DSJC0500.9.txt': 9.31760311126709, 'DSJC1000.5.txt': 69.04426693916321}\n",
+      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.057862043380737305, 'DSJC1000.9.txt': 0.21670818328857422, 'DSJC0500.1.txt': 0.027055978775024414, 'DSJC0250.1.txt': 0.005907773971557617, 'DSJC0125.9.txt': 0.0018310546875, 'DSJC0250.5.txt': 0.006178855895996094, 'DSJC0125.5.txt': 0.0016169548034667969, 'DSJC0250.9.txt': 0.006543159484863281, 'DSJC0125.1.txt': 0.0015578269958496094, 'DSJC1000.1.txt': 0.19445085525512695, 'DSJC0500.9.txt': 0.026648759841918945, 'DSJC1000.5.txt': 0.10271525382995605}\n",
+      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 18.20269513130188, 'DSJC1000.9.txt': 122.60140109062195, 'DSJC0500.1.txt': 8.298484086990356, 'DSJC0250.1.txt': 0.9747259616851807, 'DSJC0125.9.txt': 0.17962121963500977, 'DSJC0250.5.txt': 1.2000939846038818, 'DSJC0125.5.txt': 0.15546917915344238, 'DSJC0250.9.txt': 1.4175689220428467, 'DSJC0125.1.txt': 0.2008528709411621, 'DSJC1000.1.txt': 67.5939428806305, 'DSJC0500.9.txt': 11.530013084411621, 'DSJC1000.5.txt': 86.28894186019897}\n",
+      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.09375882148742676, 'DSJC1000.9.txt': 1.1257750988006592, 'DSJC0500.1.txt': 0.005967140197753906, 'DSJC0250.1.txt': 0.0014951229095458984, 'DSJC0125.9.txt': 0.0046842098236083984, 'DSJC0250.5.txt': 0.008018016815185547, 'DSJC0125.5.txt': 0.0017600059509277344, 'DSJC0250.9.txt': 0.02807331085205078, 'DSJC0125.1.txt': 0.0006096363067626953, 'DSJC1000.1.txt': 0.03177499771118164, 'DSJC0500.9.txt': 0.15678906440734863, 'DSJC1000.5.txt': 0.25353002548217773}\n",
+      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.27809929847717285, 'DSJC1000.9.txt': 0.6846380233764648, 'DSJC0500.1.txt': 0.03948807716369629, 'DSJC0250.1.txt': 0.008155107498168945, 'DSJC0125.9.txt': 0.008310079574584961, 'DSJC0250.5.txt': 0.02069091796875, 'DSJC0125.5.txt': 0.005082130432128906, 'DSJC0250.9.txt': 0.03608989715576172, 'DSJC0125.1.txt': 0.005899906158447266, 'DSJC1000.1.txt': 0.13730883598327637, 'DSJC0500.9.txt': 0.1533823013305664, 'DSJC1000.5.txt': 0.3924710750579834}\n",
+      "  Greedy: 执行时间 = {'DSJC0500.5.txt': 0.04168081283569336, 'DSJC1000.9.txt': 0.08718514442443848, 'DSJC0500.1.txt': 0.02080392837524414, 'DSJC0250.1.txt': 0.004765987396240234, 'DSJC0125.9.txt': 0.0015120506286621094, 'DSJC0250.5.txt': 0.005215167999267578, 'DSJC0125.5.txt': 0.0014150142669677734, 'DSJC0250.9.txt': 0.005381107330322266, 'DSJC0125.1.txt': 0.0027589797973632812, 'DSJC1000.1.txt': 0.07802486419677734, 'DSJC0500.9.txt': 0.02198195457458496, 'DSJC1000.5.txt': 0.08238601684570312}\n",
+      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.0707998275756836, 'DSJC1000.9.txt': 0.491008996963501, 'DSJC0500.1.txt': 0.01932525634765625, 'DSJC0250.1.txt': 0.004117012023925781, 'DSJC0125.9.txt': 0.002706766128540039, 'DSJC0250.5.txt': 0.0064661502838134766, 'DSJC0125.5.txt': 0.0013499259948730469, 'DSJC0250.9.txt': 0.013007879257202148, 'DSJC0125.1.txt': 0.002179861068725586, 'DSJC1000.1.txt': 0.0838019847869873, 'DSJC0500.9.txt': 0.08063507080078125, 'DSJC1000.5.txt': 0.18603014945983887}\n",
+      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 13.63444995880127, 'DSJC1000.9.txt': 61.64974927902222, 'DSJC0500.1.txt': 7.514086961746216, 'DSJC0250.1.txt': 0.8288030624389648, 'DSJC0125.9.txt': 0.12142586708068848, 'DSJC0250.5.txt': 0.9142141342163086, 'DSJC0125.5.txt': 0.13076090812683105, 'DSJC0250.9.txt': 0.9776561260223389, 'DSJC0125.1.txt': 0.20984697341918945, 'DSJC1000.1.txt': 57.11710214614868, 'DSJC0500.9.txt': 7.5806498527526855, 'DSJC1000.5.txt': 62.13368821144104}\n",
       "\n",
       "MEoH-MCP:\n",
       "  DSJC0500.5.txt: 使用颜色数 = 72\n",
@@ -459,15 +438,36 @@
       "  DSJC1000.1.txt: 使用颜色数 = 31\n",
       "  DSJC0500.9.txt: 使用颜色数 = 175\n",
       "  DSJC1000.5.txt: 使用颜色数 = 127\n",
-      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.053112030029296875, 'DSJC1000.9.txt': 0.19205880165100098, 'DSJC0500.1.txt': 0.027337312698364258, 'DSJC0250.1.txt': 0.01080775260925293, 'DSJC0125.9.txt': 0.0036962032318115234, 'DSJC0250.5.txt': 0.011050939559936523, 'DSJC0125.5.txt': 0.0036878585815429688, 'DSJC0250.9.txt': 0.013804912567138672, 'DSJC0125.1.txt': 0.0032007694244384766, 'DSJC1000.1.txt': 0.18375301361083984, 'DSJC0500.9.txt': 0.05500006675720215, 'DSJC1000.5.txt': 0.1247410774230957}\n",
-      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 17.517324686050415, 'DSJC1000.9.txt': 141.44973587989807, 'DSJC0500.1.txt': 9.161540746688843, 'DSJC0250.1.txt': 1.9121909141540527, 'DSJC0125.9.txt': 0.3752713203430176, 'DSJC0250.5.txt': 2.381682872772217, 'DSJC0125.5.txt': 0.3251969814300537, 'DSJC0250.9.txt': 2.7875781059265137, 'DSJC0125.1.txt': 0.2459268569946289, 'DSJC1000.1.txt': 80.19077229499817, 'DSJC0500.9.txt': 21.52015209197998, 'DSJC1000.5.txt': 122.0817620754242}\n",
-      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.23422980308532715, 'DSJC1000.9.txt': 0.7749209403991699, 'DSJC0500.1.txt': 0.04343390464782715, 'DSJC0250.1.txt': 0.024243831634521484, 'DSJC0125.9.txt': 0.015971660614013672, 'DSJC0250.5.txt': 0.05388021469116211, 'DSJC0125.5.txt': 0.009436845779418945, 'DSJC0250.9.txt': 0.0881800651550293, 'DSJC0125.1.txt': 0.006103992462158203, 'DSJC1000.1.txt': 0.13647675514221191, 'DSJC0500.9.txt': 0.16518092155456543, 'DSJC1000.5.txt': 0.9329369068145752}\n",
-      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.07716202735900879, 'DSJC1000.9.txt': 1.1940302848815918, 'DSJC0500.1.txt': 0.006262063980102539, 'DSJC0250.1.txt': 0.004677772521972656, 'DSJC0125.9.txt': 0.011601924896240234, 'DSJC0250.5.txt': 0.016296863555908203, 'DSJC0125.5.txt': 0.0036668777465820312, 'DSJC0250.9.txt': 0.062290191650390625, 'DSJC0125.1.txt': 0.0006039142608642578, 'DSJC1000.1.txt': 0.02557992935180664, 'DSJC0500.9.txt': 0.21206116676330566, 'DSJC1000.5.txt': 0.48981499671936035}\n",
-      "  贪心: 执行时间 = {'DSJC0500.5.txt': 0.0383601188659668, 'DSJC1000.9.txt': 0.12301898002624512, 'DSJC0500.1.txt': 0.020846843719482422, 'DSJC0250.1.txt': 0.009821891784667969, 'DSJC0125.9.txt': 0.002260923385620117, 'DSJC0250.5.txt': 0.010657072067260742, 'DSJC0125.5.txt': 0.0022068023681640625, 'DSJC0250.9.txt': 0.009806156158447266, 'DSJC0125.1.txt': 0.0021581649780273438, 'DSJC1000.1.txt': 0.07824492454528809, 'DSJC0500.9.txt': 0.024803876876831055, 'DSJC1000.5.txt': 0.17168307304382324}\n",
-      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.06465888023376465, 'DSJC1000.9.txt': 0.5991549491882324, 'DSJC0500.1.txt': 0.018989086151123047, 'DSJC0250.1.txt': 0.008564233779907227, 'DSJC0125.9.txt': 0.006818056106567383, 'DSJC0250.5.txt': 0.015928030014038086, 'DSJC0125.5.txt': 0.0034928321838378906, 'DSJC0250.9.txt': 0.027268171310424805, 'DSJC0125.1.txt': 0.0017459392547607422, 'DSJC1000.1.txt': 0.08201384544372559, 'DSJC0500.9.txt': 0.0891120433807373, 'DSJC1000.5.txt': 0.36855101585388184}\n",
-      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 12.905187129974365, 'DSJC1000.9.txt': 62.964935064315796, 'DSJC0500.1.txt': 8.425614833831787, 'DSJC0250.1.txt': 1.6975018978118896, 'DSJC0125.9.txt': 0.216688871383667, 'DSJC0250.5.txt': 1.7534830570220947, 'DSJC0125.5.txt': 0.2310791015625, 'DSJC0250.9.txt': 1.9282159805297852, 'DSJC0125.1.txt': 0.20327496528625488, 'DSJC1000.1.txt': 67.10282707214355, 'DSJC0500.9.txt': 9.31760311126709, 'DSJC1000.5.txt': 69.04426693916321}\n",
+      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.057862043380737305, 'DSJC1000.9.txt': 0.21670818328857422, 'DSJC0500.1.txt': 0.027055978775024414, 'DSJC0250.1.txt': 0.005907773971557617, 'DSJC0125.9.txt': 0.0018310546875, 'DSJC0250.5.txt': 0.006178855895996094, 'DSJC0125.5.txt': 0.0016169548034667969, 'DSJC0250.9.txt': 0.006543159484863281, 'DSJC0125.1.txt': 0.0015578269958496094, 'DSJC1000.1.txt': 0.19445085525512695, 'DSJC0500.9.txt': 0.026648759841918945, 'DSJC1000.5.txt': 0.10271525382995605}\n",
+      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 18.20269513130188, 'DSJC1000.9.txt': 122.60140109062195, 'DSJC0500.1.txt': 8.298484086990356, 'DSJC0250.1.txt': 0.9747259616851807, 'DSJC0125.9.txt': 0.17962121963500977, 'DSJC0250.5.txt': 1.2000939846038818, 'DSJC0125.5.txt': 0.15546917915344238, 'DSJC0250.9.txt': 1.4175689220428467, 'DSJC0125.1.txt': 0.2008528709411621, 'DSJC1000.1.txt': 67.5939428806305, 'DSJC0500.9.txt': 11.530013084411621, 'DSJC1000.5.txt': 86.28894186019897}\n",
+      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.09375882148742676, 'DSJC1000.9.txt': 1.1257750988006592, 'DSJC0500.1.txt': 0.005967140197753906, 'DSJC0250.1.txt': 0.0014951229095458984, 'DSJC0125.9.txt': 0.0046842098236083984, 'DSJC0250.5.txt': 0.008018016815185547, 'DSJC0125.5.txt': 0.0017600059509277344, 'DSJC0250.9.txt': 0.02807331085205078, 'DSJC0125.1.txt': 0.0006096363067626953, 'DSJC1000.1.txt': 0.03177499771118164, 'DSJC0500.9.txt': 0.15678906440734863, 'DSJC1000.5.txt': 0.25353002548217773}\n",
+      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.27809929847717285, 'DSJC1000.9.txt': 0.6846380233764648, 'DSJC0500.1.txt': 0.03948807716369629, 'DSJC0250.1.txt': 0.008155107498168945, 'DSJC0125.9.txt': 0.008310079574584961, 'DSJC0250.5.txt': 0.02069091796875, 'DSJC0125.5.txt': 0.005082130432128906, 'DSJC0250.9.txt': 0.03608989715576172, 'DSJC0125.1.txt': 0.005899906158447266, 'DSJC1000.1.txt': 0.13730883598327637, 'DSJC0500.9.txt': 0.1533823013305664, 'DSJC1000.5.txt': 0.3924710750579834}\n",
+      "  Greedy: 执行时间 = {'DSJC0500.5.txt': 0.04168081283569336, 'DSJC1000.9.txt': 0.08718514442443848, 'DSJC0500.1.txt': 0.02080392837524414, 'DSJC0250.1.txt': 0.004765987396240234, 'DSJC0125.9.txt': 0.0015120506286621094, 'DSJC0250.5.txt': 0.005215167999267578, 'DSJC0125.5.txt': 0.0014150142669677734, 'DSJC0250.9.txt': 0.005381107330322266, 'DSJC0125.1.txt': 0.0027589797973632812, 'DSJC1000.1.txt': 0.07802486419677734, 'DSJC0500.9.txt': 0.02198195457458496, 'DSJC1000.5.txt': 0.08238601684570312}\n",
+      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.0707998275756836, 'DSJC1000.9.txt': 0.491008996963501, 'DSJC0500.1.txt': 0.01932525634765625, 'DSJC0250.1.txt': 0.004117012023925781, 'DSJC0125.9.txt': 0.002706766128540039, 'DSJC0250.5.txt': 0.0064661502838134766, 'DSJC0125.5.txt': 0.0013499259948730469, 'DSJC0250.9.txt': 0.013007879257202148, 'DSJC0125.1.txt': 0.002179861068725586, 'DSJC1000.1.txt': 0.0838019847869873, 'DSJC0500.9.txt': 0.08063507080078125, 'DSJC1000.5.txt': 0.18603014945983887}\n",
+      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 13.63444995880127, 'DSJC1000.9.txt': 61.64974927902222, 'DSJC0500.1.txt': 7.514086961746216, 'DSJC0250.1.txt': 0.8288030624389648, 'DSJC0125.9.txt': 0.12142586708068848, 'DSJC0250.5.txt': 0.9142141342163086, 'DSJC0125.5.txt': 0.13076090812683105, 'DSJC0250.9.txt': 0.9776561260223389, 'DSJC0125.1.txt': 0.20984697341918945, 'DSJC1000.1.txt': 57.11710214614868, 'DSJC0500.9.txt': 7.5806498527526855, 'DSJC1000.5.txt': 62.13368821144104}\n",
       "\n",
-      "贪心:\n",
+      "AAE-MCP:\n",
+      "  DSJC0500.5.txt: 使用颜色数 = 65\n",
+      "  DSJC1000.9.txt: 使用颜色数 = 299\n",
+      "  DSJC0500.1.txt: 使用颜色数 = 16\n",
+      "  DSJC0250.1.txt: 使用颜色数 = 10\n",
+      "  DSJC0125.9.txt: 使用颜色数 = 51\n",
+      "  DSJC0250.5.txt: 使用颜色数 = 37\n",
+      "  DSJC0125.5.txt: 使用颜色数 = 22\n",
+      "  DSJC0250.9.txt: 使用颜色数 = 92\n",
+      "  DSJC0125.1.txt: 使用颜色数 = 6\n",
+      "  DSJC1000.1.txt: 使用颜色数 = 27\n",
+      "  DSJC0500.9.txt: 使用颜色数 = 170\n",
+      "  DSJC1000.5.txt: 使用颜色数 = 115\n",
+      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.057862043380737305, 'DSJC1000.9.txt': 0.21670818328857422, 'DSJC0500.1.txt': 0.027055978775024414, 'DSJC0250.1.txt': 0.005907773971557617, 'DSJC0125.9.txt': 0.0018310546875, 'DSJC0250.5.txt': 0.006178855895996094, 'DSJC0125.5.txt': 0.0016169548034667969, 'DSJC0250.9.txt': 0.006543159484863281, 'DSJC0125.1.txt': 0.0015578269958496094, 'DSJC1000.1.txt': 0.19445085525512695, 'DSJC0500.9.txt': 0.026648759841918945, 'DSJC1000.5.txt': 0.10271525382995605}\n",
+      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 18.20269513130188, 'DSJC1000.9.txt': 122.60140109062195, 'DSJC0500.1.txt': 8.298484086990356, 'DSJC0250.1.txt': 0.9747259616851807, 'DSJC0125.9.txt': 0.17962121963500977, 'DSJC0250.5.txt': 1.2000939846038818, 'DSJC0125.5.txt': 0.15546917915344238, 'DSJC0250.9.txt': 1.4175689220428467, 'DSJC0125.1.txt': 0.2008528709411621, 'DSJC1000.1.txt': 67.5939428806305, 'DSJC0500.9.txt': 11.530013084411621, 'DSJC1000.5.txt': 86.28894186019897}\n",
+      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.09375882148742676, 'DSJC1000.9.txt': 1.1257750988006592, 'DSJC0500.1.txt': 0.005967140197753906, 'DSJC0250.1.txt': 0.0014951229095458984, 'DSJC0125.9.txt': 0.0046842098236083984, 'DSJC0250.5.txt': 0.008018016815185547, 'DSJC0125.5.txt': 0.0017600059509277344, 'DSJC0250.9.txt': 0.02807331085205078, 'DSJC0125.1.txt': 0.0006096363067626953, 'DSJC1000.1.txt': 0.03177499771118164, 'DSJC0500.9.txt': 0.15678906440734863, 'DSJC1000.5.txt': 0.25353002548217773}\n",
+      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.27809929847717285, 'DSJC1000.9.txt': 0.6846380233764648, 'DSJC0500.1.txt': 0.03948807716369629, 'DSJC0250.1.txt': 0.008155107498168945, 'DSJC0125.9.txt': 0.008310079574584961, 'DSJC0250.5.txt': 0.02069091796875, 'DSJC0125.5.txt': 0.005082130432128906, 'DSJC0250.9.txt': 0.03608989715576172, 'DSJC0125.1.txt': 0.005899906158447266, 'DSJC1000.1.txt': 0.13730883598327637, 'DSJC0500.9.txt': 0.1533823013305664, 'DSJC1000.5.txt': 0.3924710750579834}\n",
+      "  Greedy: 执行时间 = {'DSJC0500.5.txt': 0.04168081283569336, 'DSJC1000.9.txt': 0.08718514442443848, 'DSJC0500.1.txt': 0.02080392837524414, 'DSJC0250.1.txt': 0.004765987396240234, 'DSJC0125.9.txt': 0.0015120506286621094, 'DSJC0250.5.txt': 0.005215167999267578, 'DSJC0125.5.txt': 0.0014150142669677734, 'DSJC0250.9.txt': 0.005381107330322266, 'DSJC0125.1.txt': 0.0027589797973632812, 'DSJC1000.1.txt': 0.07802486419677734, 'DSJC0500.9.txt': 0.02198195457458496, 'DSJC1000.5.txt': 0.08238601684570312}\n",
+      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.0707998275756836, 'DSJC1000.9.txt': 0.491008996963501, 'DSJC0500.1.txt': 0.01932525634765625, 'DSJC0250.1.txt': 0.004117012023925781, 'DSJC0125.9.txt': 0.002706766128540039, 'DSJC0250.5.txt': 0.0064661502838134766, 'DSJC0125.5.txt': 0.0013499259948730469, 'DSJC0250.9.txt': 0.013007879257202148, 'DSJC0125.1.txt': 0.002179861068725586, 'DSJC1000.1.txt': 0.0838019847869873, 'DSJC0500.9.txt': 0.08063507080078125, 'DSJC1000.5.txt': 0.18603014945983887}\n",
+      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 13.63444995880127, 'DSJC1000.9.txt': 61.64974927902222, 'DSJC0500.1.txt': 7.514086961746216, 'DSJC0250.1.txt': 0.8288030624389648, 'DSJC0125.9.txt': 0.12142586708068848, 'DSJC0250.5.txt': 0.9142141342163086, 'DSJC0125.5.txt': 0.13076090812683105, 'DSJC0250.9.txt': 0.9776561260223389, 'DSJC0125.1.txt': 0.20984697341918945, 'DSJC1000.1.txt': 57.11710214614868, 'DSJC0500.9.txt': 7.5806498527526855, 'DSJC1000.5.txt': 62.13368821144104}\n",
+      "\n",
+      "Greedy:\n",
       "  DSJC0500.5.txt: 使用颜色数 = 72\n",
       "  DSJC1000.9.txt: 使用颜色数 = 321\n",
       "  DSJC0500.1.txt: 使用颜色数 = 20\n",
@@ -480,13 +480,13 @@
       "  DSJC1000.1.txt: 使用颜色数 = 31\n",
       "  DSJC0500.9.txt: 使用颜色数 = 175\n",
       "  DSJC1000.5.txt: 使用颜色数 = 127\n",
-      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.053112030029296875, 'DSJC1000.9.txt': 0.19205880165100098, 'DSJC0500.1.txt': 0.027337312698364258, 'DSJC0250.1.txt': 0.01080775260925293, 'DSJC0125.9.txt': 0.0036962032318115234, 'DSJC0250.5.txt': 0.011050939559936523, 'DSJC0125.5.txt': 0.0036878585815429688, 'DSJC0250.9.txt': 0.013804912567138672, 'DSJC0125.1.txt': 0.0032007694244384766, 'DSJC1000.1.txt': 0.18375301361083984, 'DSJC0500.9.txt': 0.05500006675720215, 'DSJC1000.5.txt': 0.1247410774230957}\n",
-      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 17.517324686050415, 'DSJC1000.9.txt': 141.44973587989807, 'DSJC0500.1.txt': 9.161540746688843, 'DSJC0250.1.txt': 1.9121909141540527, 'DSJC0125.9.txt': 0.3752713203430176, 'DSJC0250.5.txt': 2.381682872772217, 'DSJC0125.5.txt': 0.3251969814300537, 'DSJC0250.9.txt': 2.7875781059265137, 'DSJC0125.1.txt': 0.2459268569946289, 'DSJC1000.1.txt': 80.19077229499817, 'DSJC0500.9.txt': 21.52015209197998, 'DSJC1000.5.txt': 122.0817620754242}\n",
-      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.23422980308532715, 'DSJC1000.9.txt': 0.7749209403991699, 'DSJC0500.1.txt': 0.04343390464782715, 'DSJC0250.1.txt': 0.024243831634521484, 'DSJC0125.9.txt': 0.015971660614013672, 'DSJC0250.5.txt': 0.05388021469116211, 'DSJC0125.5.txt': 0.009436845779418945, 'DSJC0250.9.txt': 0.0881800651550293, 'DSJC0125.1.txt': 0.006103992462158203, 'DSJC1000.1.txt': 0.13647675514221191, 'DSJC0500.9.txt': 0.16518092155456543, 'DSJC1000.5.txt': 0.9329369068145752}\n",
-      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.07716202735900879, 'DSJC1000.9.txt': 1.1940302848815918, 'DSJC0500.1.txt': 0.006262063980102539, 'DSJC0250.1.txt': 0.004677772521972656, 'DSJC0125.9.txt': 0.011601924896240234, 'DSJC0250.5.txt': 0.016296863555908203, 'DSJC0125.5.txt': 0.0036668777465820312, 'DSJC0250.9.txt': 0.062290191650390625, 'DSJC0125.1.txt': 0.0006039142608642578, 'DSJC1000.1.txt': 0.02557992935180664, 'DSJC0500.9.txt': 0.21206116676330566, 'DSJC1000.5.txt': 0.48981499671936035}\n",
-      "  贪心: 执行时间 = {'DSJC0500.5.txt': 0.0383601188659668, 'DSJC1000.9.txt': 0.12301898002624512, 'DSJC0500.1.txt': 0.020846843719482422, 'DSJC0250.1.txt': 0.009821891784667969, 'DSJC0125.9.txt': 0.002260923385620117, 'DSJC0250.5.txt': 0.010657072067260742, 'DSJC0125.5.txt': 0.0022068023681640625, 'DSJC0250.9.txt': 0.009806156158447266, 'DSJC0125.1.txt': 0.0021581649780273438, 'DSJC1000.1.txt': 0.07824492454528809, 'DSJC0500.9.txt': 0.024803876876831055, 'DSJC1000.5.txt': 0.17168307304382324}\n",
-      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.06465888023376465, 'DSJC1000.9.txt': 0.5991549491882324, 'DSJC0500.1.txt': 0.018989086151123047, 'DSJC0250.1.txt': 0.008564233779907227, 'DSJC0125.9.txt': 0.006818056106567383, 'DSJC0250.5.txt': 0.015928030014038086, 'DSJC0125.5.txt': 0.0034928321838378906, 'DSJC0250.9.txt': 0.027268171310424805, 'DSJC0125.1.txt': 0.0017459392547607422, 'DSJC1000.1.txt': 0.08201384544372559, 'DSJC0500.9.txt': 0.0891120433807373, 'DSJC1000.5.txt': 0.36855101585388184}\n",
-      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 12.905187129974365, 'DSJC1000.9.txt': 62.964935064315796, 'DSJC0500.1.txt': 8.425614833831787, 'DSJC0250.1.txt': 1.6975018978118896, 'DSJC0125.9.txt': 0.216688871383667, 'DSJC0250.5.txt': 1.7534830570220947, 'DSJC0125.5.txt': 0.2310791015625, 'DSJC0250.9.txt': 1.9282159805297852, 'DSJC0125.1.txt': 0.20327496528625488, 'DSJC1000.1.txt': 67.10282707214355, 'DSJC0500.9.txt': 9.31760311126709, 'DSJC1000.5.txt': 69.04426693916321}\n",
+      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.057862043380737305, 'DSJC1000.9.txt': 0.21670818328857422, 'DSJC0500.1.txt': 0.027055978775024414, 'DSJC0250.1.txt': 0.005907773971557617, 'DSJC0125.9.txt': 0.0018310546875, 'DSJC0250.5.txt': 0.006178855895996094, 'DSJC0125.5.txt': 0.0016169548034667969, 'DSJC0250.9.txt': 0.006543159484863281, 'DSJC0125.1.txt': 0.0015578269958496094, 'DSJC1000.1.txt': 0.19445085525512695, 'DSJC0500.9.txt': 0.026648759841918945, 'DSJC1000.5.txt': 0.10271525382995605}\n",
+      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 18.20269513130188, 'DSJC1000.9.txt': 122.60140109062195, 'DSJC0500.1.txt': 8.298484086990356, 'DSJC0250.1.txt': 0.9747259616851807, 'DSJC0125.9.txt': 0.17962121963500977, 'DSJC0250.5.txt': 1.2000939846038818, 'DSJC0125.5.txt': 0.15546917915344238, 'DSJC0250.9.txt': 1.4175689220428467, 'DSJC0125.1.txt': 0.2008528709411621, 'DSJC1000.1.txt': 67.5939428806305, 'DSJC0500.9.txt': 11.530013084411621, 'DSJC1000.5.txt': 86.28894186019897}\n",
+      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.09375882148742676, 'DSJC1000.9.txt': 1.1257750988006592, 'DSJC0500.1.txt': 0.005967140197753906, 'DSJC0250.1.txt': 0.0014951229095458984, 'DSJC0125.9.txt': 0.0046842098236083984, 'DSJC0250.5.txt': 0.008018016815185547, 'DSJC0125.5.txt': 0.0017600059509277344, 'DSJC0250.9.txt': 0.02807331085205078, 'DSJC0125.1.txt': 0.0006096363067626953, 'DSJC1000.1.txt': 0.03177499771118164, 'DSJC0500.9.txt': 0.15678906440734863, 'DSJC1000.5.txt': 0.25353002548217773}\n",
+      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.27809929847717285, 'DSJC1000.9.txt': 0.6846380233764648, 'DSJC0500.1.txt': 0.03948807716369629, 'DSJC0250.1.txt': 0.008155107498168945, 'DSJC0125.9.txt': 0.008310079574584961, 'DSJC0250.5.txt': 0.02069091796875, 'DSJC0125.5.txt': 0.005082130432128906, 'DSJC0250.9.txt': 0.03608989715576172, 'DSJC0125.1.txt': 0.005899906158447266, 'DSJC1000.1.txt': 0.13730883598327637, 'DSJC0500.9.txt': 0.1533823013305664, 'DSJC1000.5.txt': 0.3924710750579834}\n",
+      "  Greedy: 执行时间 = {'DSJC0500.5.txt': 0.04168081283569336, 'DSJC1000.9.txt': 0.08718514442443848, 'DSJC0500.1.txt': 0.02080392837524414, 'DSJC0250.1.txt': 0.004765987396240234, 'DSJC0125.9.txt': 0.0015120506286621094, 'DSJC0250.5.txt': 0.005215167999267578, 'DSJC0125.5.txt': 0.0014150142669677734, 'DSJC0250.9.txt': 0.005381107330322266, 'DSJC0125.1.txt': 0.0027589797973632812, 'DSJC1000.1.txt': 0.07802486419677734, 'DSJC0500.9.txt': 0.02198195457458496, 'DSJC1000.5.txt': 0.08238601684570312}\n",
+      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.0707998275756836, 'DSJC1000.9.txt': 0.491008996963501, 'DSJC0500.1.txt': 0.01932525634765625, 'DSJC0250.1.txt': 0.004117012023925781, 'DSJC0125.9.txt': 0.002706766128540039, 'DSJC0250.5.txt': 0.0064661502838134766, 'DSJC0125.5.txt': 0.0013499259948730469, 'DSJC0250.9.txt': 0.013007879257202148, 'DSJC0125.1.txt': 0.002179861068725586, 'DSJC1000.1.txt': 0.0838019847869873, 'DSJC0500.9.txt': 0.08063507080078125, 'DSJC1000.5.txt': 0.18603014945983887}\n",
+      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 13.63444995880127, 'DSJC1000.9.txt': 61.64974927902222, 'DSJC0500.1.txt': 7.514086961746216, 'DSJC0250.1.txt': 0.8288030624389648, 'DSJC0125.9.txt': 0.12142586708068848, 'DSJC0250.5.txt': 0.9142141342163086, 'DSJC0125.5.txt': 0.13076090812683105, 'DSJC0250.9.txt': 0.9776561260223389, 'DSJC0125.1.txt': 0.20984697341918945, 'DSJC1000.1.txt': 57.11710214614868, 'DSJC0500.9.txt': 7.5806498527526855, 'DSJC1000.5.txt': 62.13368821144104}\n",
       "\n",
       "Welsh-Powell:\n",
       "  DSJC0500.5.txt: 使用颜色数 = 71\n",
@@ -501,13 +501,13 @@
       "  DSJC1000.1.txt: 使用颜色数 = 29\n",
       "  DSJC0500.9.txt: 使用颜色数 = 169\n",
       "  DSJC1000.5.txt: 使用颜色数 = 121\n",
-      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.053112030029296875, 'DSJC1000.9.txt': 0.19205880165100098, 'DSJC0500.1.txt': 0.027337312698364258, 'DSJC0250.1.txt': 0.01080775260925293, 'DSJC0125.9.txt': 0.0036962032318115234, 'DSJC0250.5.txt': 0.011050939559936523, 'DSJC0125.5.txt': 0.0036878585815429688, 'DSJC0250.9.txt': 0.013804912567138672, 'DSJC0125.1.txt': 0.0032007694244384766, 'DSJC1000.1.txt': 0.18375301361083984, 'DSJC0500.9.txt': 0.05500006675720215, 'DSJC1000.5.txt': 0.1247410774230957}\n",
-      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 17.517324686050415, 'DSJC1000.9.txt': 141.44973587989807, 'DSJC0500.1.txt': 9.161540746688843, 'DSJC0250.1.txt': 1.9121909141540527, 'DSJC0125.9.txt': 0.3752713203430176, 'DSJC0250.5.txt': 2.381682872772217, 'DSJC0125.5.txt': 0.3251969814300537, 'DSJC0250.9.txt': 2.7875781059265137, 'DSJC0125.1.txt': 0.2459268569946289, 'DSJC1000.1.txt': 80.19077229499817, 'DSJC0500.9.txt': 21.52015209197998, 'DSJC1000.5.txt': 122.0817620754242}\n",
-      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.23422980308532715, 'DSJC1000.9.txt': 0.7749209403991699, 'DSJC0500.1.txt': 0.04343390464782715, 'DSJC0250.1.txt': 0.024243831634521484, 'DSJC0125.9.txt': 0.015971660614013672, 'DSJC0250.5.txt': 0.05388021469116211, 'DSJC0125.5.txt': 0.009436845779418945, 'DSJC0250.9.txt': 0.0881800651550293, 'DSJC0125.1.txt': 0.006103992462158203, 'DSJC1000.1.txt': 0.13647675514221191, 'DSJC0500.9.txt': 0.16518092155456543, 'DSJC1000.5.txt': 0.9329369068145752}\n",
-      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.07716202735900879, 'DSJC1000.9.txt': 1.1940302848815918, 'DSJC0500.1.txt': 0.006262063980102539, 'DSJC0250.1.txt': 0.004677772521972656, 'DSJC0125.9.txt': 0.011601924896240234, 'DSJC0250.5.txt': 0.016296863555908203, 'DSJC0125.5.txt': 0.0036668777465820312, 'DSJC0250.9.txt': 0.062290191650390625, 'DSJC0125.1.txt': 0.0006039142608642578, 'DSJC1000.1.txt': 0.02557992935180664, 'DSJC0500.9.txt': 0.21206116676330566, 'DSJC1000.5.txt': 0.48981499671936035}\n",
-      "  贪心: 执行时间 = {'DSJC0500.5.txt': 0.0383601188659668, 'DSJC1000.9.txt': 0.12301898002624512, 'DSJC0500.1.txt': 0.020846843719482422, 'DSJC0250.1.txt': 0.009821891784667969, 'DSJC0125.9.txt': 0.002260923385620117, 'DSJC0250.5.txt': 0.010657072067260742, 'DSJC0125.5.txt': 0.0022068023681640625, 'DSJC0250.9.txt': 0.009806156158447266, 'DSJC0125.1.txt': 0.0021581649780273438, 'DSJC1000.1.txt': 0.07824492454528809, 'DSJC0500.9.txt': 0.024803876876831055, 'DSJC1000.5.txt': 0.17168307304382324}\n",
-      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.06465888023376465, 'DSJC1000.9.txt': 0.5991549491882324, 'DSJC0500.1.txt': 0.018989086151123047, 'DSJC0250.1.txt': 0.008564233779907227, 'DSJC0125.9.txt': 0.006818056106567383, 'DSJC0250.5.txt': 0.015928030014038086, 'DSJC0125.5.txt': 0.0034928321838378906, 'DSJC0250.9.txt': 0.027268171310424805, 'DSJC0125.1.txt': 0.0017459392547607422, 'DSJC1000.1.txt': 0.08201384544372559, 'DSJC0500.9.txt': 0.0891120433807373, 'DSJC1000.5.txt': 0.36855101585388184}\n",
-      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 12.905187129974365, 'DSJC1000.9.txt': 62.964935064315796, 'DSJC0500.1.txt': 8.425614833831787, 'DSJC0250.1.txt': 1.6975018978118896, 'DSJC0125.9.txt': 0.216688871383667, 'DSJC0250.5.txt': 1.7534830570220947, 'DSJC0125.5.txt': 0.2310791015625, 'DSJC0250.9.txt': 1.9282159805297852, 'DSJC0125.1.txt': 0.20327496528625488, 'DSJC1000.1.txt': 67.10282707214355, 'DSJC0500.9.txt': 9.31760311126709, 'DSJC1000.5.txt': 69.04426693916321}\n",
+      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.057862043380737305, 'DSJC1000.9.txt': 0.21670818328857422, 'DSJC0500.1.txt': 0.027055978775024414, 'DSJC0250.1.txt': 0.005907773971557617, 'DSJC0125.9.txt': 0.0018310546875, 'DSJC0250.5.txt': 0.006178855895996094, 'DSJC0125.5.txt': 0.0016169548034667969, 'DSJC0250.9.txt': 0.006543159484863281, 'DSJC0125.1.txt': 0.0015578269958496094, 'DSJC1000.1.txt': 0.19445085525512695, 'DSJC0500.9.txt': 0.026648759841918945, 'DSJC1000.5.txt': 0.10271525382995605}\n",
+      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 18.20269513130188, 'DSJC1000.9.txt': 122.60140109062195, 'DSJC0500.1.txt': 8.298484086990356, 'DSJC0250.1.txt': 0.9747259616851807, 'DSJC0125.9.txt': 0.17962121963500977, 'DSJC0250.5.txt': 1.2000939846038818, 'DSJC0125.5.txt': 0.15546917915344238, 'DSJC0250.9.txt': 1.4175689220428467, 'DSJC0125.1.txt': 0.2008528709411621, 'DSJC1000.1.txt': 67.5939428806305, 'DSJC0500.9.txt': 11.530013084411621, 'DSJC1000.5.txt': 86.28894186019897}\n",
+      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.09375882148742676, 'DSJC1000.9.txt': 1.1257750988006592, 'DSJC0500.1.txt': 0.005967140197753906, 'DSJC0250.1.txt': 0.0014951229095458984, 'DSJC0125.9.txt': 0.0046842098236083984, 'DSJC0250.5.txt': 0.008018016815185547, 'DSJC0125.5.txt': 0.0017600059509277344, 'DSJC0250.9.txt': 0.02807331085205078, 'DSJC0125.1.txt': 0.0006096363067626953, 'DSJC1000.1.txt': 0.03177499771118164, 'DSJC0500.9.txt': 0.15678906440734863, 'DSJC1000.5.txt': 0.25353002548217773}\n",
+      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.27809929847717285, 'DSJC1000.9.txt': 0.6846380233764648, 'DSJC0500.1.txt': 0.03948807716369629, 'DSJC0250.1.txt': 0.008155107498168945, 'DSJC0125.9.txt': 0.008310079574584961, 'DSJC0250.5.txt': 0.02069091796875, 'DSJC0125.5.txt': 0.005082130432128906, 'DSJC0250.9.txt': 0.03608989715576172, 'DSJC0125.1.txt': 0.005899906158447266, 'DSJC1000.1.txt': 0.13730883598327637, 'DSJC0500.9.txt': 0.1533823013305664, 'DSJC1000.5.txt': 0.3924710750579834}\n",
+      "  Greedy: 执行时间 = {'DSJC0500.5.txt': 0.04168081283569336, 'DSJC1000.9.txt': 0.08718514442443848, 'DSJC0500.1.txt': 0.02080392837524414, 'DSJC0250.1.txt': 0.004765987396240234, 'DSJC0125.9.txt': 0.0015120506286621094, 'DSJC0250.5.txt': 0.005215167999267578, 'DSJC0125.5.txt': 0.0014150142669677734, 'DSJC0250.9.txt': 0.005381107330322266, 'DSJC0125.1.txt': 0.0027589797973632812, 'DSJC1000.1.txt': 0.07802486419677734, 'DSJC0500.9.txt': 0.02198195457458496, 'DSJC1000.5.txt': 0.08238601684570312}\n",
+      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.0707998275756836, 'DSJC1000.9.txt': 0.491008996963501, 'DSJC0500.1.txt': 0.01932525634765625, 'DSJC0250.1.txt': 0.004117012023925781, 'DSJC0125.9.txt': 0.002706766128540039, 'DSJC0250.5.txt': 0.0064661502838134766, 'DSJC0125.5.txt': 0.0013499259948730469, 'DSJC0250.9.txt': 0.013007879257202148, 'DSJC0125.1.txt': 0.002179861068725586, 'DSJC1000.1.txt': 0.0838019847869873, 'DSJC0500.9.txt': 0.08063507080078125, 'DSJC1000.5.txt': 0.18603014945983887}\n",
+      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 13.63444995880127, 'DSJC1000.9.txt': 61.64974927902222, 'DSJC0500.1.txt': 7.514086961746216, 'DSJC0250.1.txt': 0.8288030624389648, 'DSJC0125.9.txt': 0.12142586708068848, 'DSJC0250.5.txt': 0.9142141342163086, 'DSJC0125.5.txt': 0.13076090812683105, 'DSJC0250.9.txt': 0.9776561260223389, 'DSJC0125.1.txt': 0.20984697341918945, 'DSJC1000.1.txt': 57.11710214614868, 'DSJC0500.9.txt': 7.5806498527526855, 'DSJC1000.5.txt': 62.13368821144104}\n",
       "\n",
       "DSATUR:\n",
       "  DSJC0500.5.txt: 使用颜色数 = 65\n",
@@ -522,13 +522,13 @@
       "  DSJC1000.1.txt: 使用颜色数 = 27\n",
       "  DSJC0500.9.txt: 使用颜色数 = 170\n",
       "  DSJC1000.5.txt: 使用颜色数 = 115\n",
-      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.053112030029296875, 'DSJC1000.9.txt': 0.19205880165100098, 'DSJC0500.1.txt': 0.027337312698364258, 'DSJC0250.1.txt': 0.01080775260925293, 'DSJC0125.9.txt': 0.0036962032318115234, 'DSJC0250.5.txt': 0.011050939559936523, 'DSJC0125.5.txt': 0.0036878585815429688, 'DSJC0250.9.txt': 0.013804912567138672, 'DSJC0125.1.txt': 0.0032007694244384766, 'DSJC1000.1.txt': 0.18375301361083984, 'DSJC0500.9.txt': 0.05500006675720215, 'DSJC1000.5.txt': 0.1247410774230957}\n",
-      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 17.517324686050415, 'DSJC1000.9.txt': 141.44973587989807, 'DSJC0500.1.txt': 9.161540746688843, 'DSJC0250.1.txt': 1.9121909141540527, 'DSJC0125.9.txt': 0.3752713203430176, 'DSJC0250.5.txt': 2.381682872772217, 'DSJC0125.5.txt': 0.3251969814300537, 'DSJC0250.9.txt': 2.7875781059265137, 'DSJC0125.1.txt': 0.2459268569946289, 'DSJC1000.1.txt': 80.19077229499817, 'DSJC0500.9.txt': 21.52015209197998, 'DSJC1000.5.txt': 122.0817620754242}\n",
-      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.23422980308532715, 'DSJC1000.9.txt': 0.7749209403991699, 'DSJC0500.1.txt': 0.04343390464782715, 'DSJC0250.1.txt': 0.024243831634521484, 'DSJC0125.9.txt': 0.015971660614013672, 'DSJC0250.5.txt': 0.05388021469116211, 'DSJC0125.5.txt': 0.009436845779418945, 'DSJC0250.9.txt': 0.0881800651550293, 'DSJC0125.1.txt': 0.006103992462158203, 'DSJC1000.1.txt': 0.13647675514221191, 'DSJC0500.9.txt': 0.16518092155456543, 'DSJC1000.5.txt': 0.9329369068145752}\n",
-      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.07716202735900879, 'DSJC1000.9.txt': 1.1940302848815918, 'DSJC0500.1.txt': 0.006262063980102539, 'DSJC0250.1.txt': 0.004677772521972656, 'DSJC0125.9.txt': 0.011601924896240234, 'DSJC0250.5.txt': 0.016296863555908203, 'DSJC0125.5.txt': 0.0036668777465820312, 'DSJC0250.9.txt': 0.062290191650390625, 'DSJC0125.1.txt': 0.0006039142608642578, 'DSJC1000.1.txt': 0.02557992935180664, 'DSJC0500.9.txt': 0.21206116676330566, 'DSJC1000.5.txt': 0.48981499671936035}\n",
-      "  贪心: 执行时间 = {'DSJC0500.5.txt': 0.0383601188659668, 'DSJC1000.9.txt': 0.12301898002624512, 'DSJC0500.1.txt': 0.020846843719482422, 'DSJC0250.1.txt': 0.009821891784667969, 'DSJC0125.9.txt': 0.002260923385620117, 'DSJC0250.5.txt': 0.010657072067260742, 'DSJC0125.5.txt': 0.0022068023681640625, 'DSJC0250.9.txt': 0.009806156158447266, 'DSJC0125.1.txt': 0.0021581649780273438, 'DSJC1000.1.txt': 0.07824492454528809, 'DSJC0500.9.txt': 0.024803876876831055, 'DSJC1000.5.txt': 0.17168307304382324}\n",
-      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.06465888023376465, 'DSJC1000.9.txt': 0.5991549491882324, 'DSJC0500.1.txt': 0.018989086151123047, 'DSJC0250.1.txt': 0.008564233779907227, 'DSJC0125.9.txt': 0.006818056106567383, 'DSJC0250.5.txt': 0.015928030014038086, 'DSJC0125.5.txt': 0.0034928321838378906, 'DSJC0250.9.txt': 0.027268171310424805, 'DSJC0125.1.txt': 0.0017459392547607422, 'DSJC1000.1.txt': 0.08201384544372559, 'DSJC0500.9.txt': 0.0891120433807373, 'DSJC1000.5.txt': 0.36855101585388184}\n",
-      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 12.905187129974365, 'DSJC1000.9.txt': 62.964935064315796, 'DSJC0500.1.txt': 8.425614833831787, 'DSJC0250.1.txt': 1.6975018978118896, 'DSJC0125.9.txt': 0.216688871383667, 'DSJC0250.5.txt': 1.7534830570220947, 'DSJC0125.5.txt': 0.2310791015625, 'DSJC0250.9.txt': 1.9282159805297852, 'DSJC0125.1.txt': 0.20327496528625488, 'DSJC1000.1.txt': 67.10282707214355, 'DSJC0500.9.txt': 9.31760311126709, 'DSJC1000.5.txt': 69.04426693916321}\n"
+      "  FunSearch-MCP: 执行时间 = {'DSJC0500.5.txt': 0.057862043380737305, 'DSJC1000.9.txt': 0.21670818328857422, 'DSJC0500.1.txt': 0.027055978775024414, 'DSJC0250.1.txt': 0.005907773971557617, 'DSJC0125.9.txt': 0.0018310546875, 'DSJC0250.5.txt': 0.006178855895996094, 'DSJC0125.5.txt': 0.0016169548034667969, 'DSJC0250.9.txt': 0.006543159484863281, 'DSJC0125.1.txt': 0.0015578269958496094, 'DSJC1000.1.txt': 0.19445085525512695, 'DSJC0500.9.txt': 0.026648759841918945, 'DSJC1000.5.txt': 0.10271525382995605}\n",
+      "  EoH-MCP: 执行时间 = {'DSJC0500.5.txt': 18.20269513130188, 'DSJC1000.9.txt': 122.60140109062195, 'DSJC0500.1.txt': 8.298484086990356, 'DSJC0250.1.txt': 0.9747259616851807, 'DSJC0125.9.txt': 0.17962121963500977, 'DSJC0250.5.txt': 1.2000939846038818, 'DSJC0125.5.txt': 0.15546917915344238, 'DSJC0250.9.txt': 1.4175689220428467, 'DSJC0125.1.txt': 0.2008528709411621, 'DSJC1000.1.txt': 67.5939428806305, 'DSJC0500.9.txt': 11.530013084411621, 'DSJC1000.5.txt': 86.28894186019897}\n",
+      "  MEoH-MCP: 执行时间 = {'DSJC0500.5.txt': 0.09375882148742676, 'DSJC1000.9.txt': 1.1257750988006592, 'DSJC0500.1.txt': 0.005967140197753906, 'DSJC0250.1.txt': 0.0014951229095458984, 'DSJC0125.9.txt': 0.0046842098236083984, 'DSJC0250.5.txt': 0.008018016815185547, 'DSJC0125.5.txt': 0.0017600059509277344, 'DSJC0250.9.txt': 0.02807331085205078, 'DSJC0125.1.txt': 0.0006096363067626953, 'DSJC1000.1.txt': 0.03177499771118164, 'DSJC0500.9.txt': 0.15678906440734863, 'DSJC1000.5.txt': 0.25353002548217773}\n",
+      "  AAE-MCP: 执行时间 = {'DSJC0500.5.txt': 0.27809929847717285, 'DSJC1000.9.txt': 0.6846380233764648, 'DSJC0500.1.txt': 0.03948807716369629, 'DSJC0250.1.txt': 0.008155107498168945, 'DSJC0125.9.txt': 0.008310079574584961, 'DSJC0250.5.txt': 0.02069091796875, 'DSJC0125.5.txt': 0.005082130432128906, 'DSJC0250.9.txt': 0.03608989715576172, 'DSJC0125.1.txt': 0.005899906158447266, 'DSJC1000.1.txt': 0.13730883598327637, 'DSJC0500.9.txt': 0.1533823013305664, 'DSJC1000.5.txt': 0.3924710750579834}\n",
+      "  Greedy: 执行时间 = {'DSJC0500.5.txt': 0.04168081283569336, 'DSJC1000.9.txt': 0.08718514442443848, 'DSJC0500.1.txt': 0.02080392837524414, 'DSJC0250.1.txt': 0.004765987396240234, 'DSJC0125.9.txt': 0.0015120506286621094, 'DSJC0250.5.txt': 0.005215167999267578, 'DSJC0125.5.txt': 0.0014150142669677734, 'DSJC0250.9.txt': 0.005381107330322266, 'DSJC0125.1.txt': 0.0027589797973632812, 'DSJC1000.1.txt': 0.07802486419677734, 'DSJC0500.9.txt': 0.02198195457458496, 'DSJC1000.5.txt': 0.08238601684570312}\n",
+      "  Welsh-Powell: 执行时间 = {'DSJC0500.5.txt': 0.0707998275756836, 'DSJC1000.9.txt': 0.491008996963501, 'DSJC0500.1.txt': 0.01932525634765625, 'DSJC0250.1.txt': 0.004117012023925781, 'DSJC0125.9.txt': 0.002706766128540039, 'DSJC0250.5.txt': 0.0064661502838134766, 'DSJC0125.5.txt': 0.0013499259948730469, 'DSJC0250.9.txt': 0.013007879257202148, 'DSJC0125.1.txt': 0.002179861068725586, 'DSJC1000.1.txt': 0.0838019847869873, 'DSJC0500.9.txt': 0.08063507080078125, 'DSJC1000.5.txt': 0.18603014945983887}\n",
+      "  DSATUR: 执行时间 = {'DSJC0500.5.txt': 13.63444995880127, 'DSJC1000.9.txt': 61.64974927902222, 'DSJC0500.1.txt': 7.514086961746216, 'DSJC0250.1.txt': 0.8288030624389648, 'DSJC0125.9.txt': 0.12142586708068848, 'DSJC0250.5.txt': 0.9142141342163086, 'DSJC0125.5.txt': 0.13076090812683105, 'DSJC0250.9.txt': 0.9776561260223389, 'DSJC0125.1.txt': 0.20984697341918945, 'DSJC1000.1.txt': 57.11710214614868, 'DSJC0500.9.txt': 7.5806498527526855, 'DSJC1000.5.txt': 62.13368821144104}\n"
      ]
     }
    ],
@@ -551,9 +551,9 @@
     "        \"FunSearch-MCP\": graph_coloring_v1,\n",
     "        \"EoH-MCP\": graph_coloring_v2, \n",
     "        # \"MCP-03\": graph_coloring_v3,\n",
-    "        \"AAE-MCP\": graph_coloring_v5,\n",
     "        \"MEoH-MCP\": graph_coloring_meoh,\n",
-    "        \"贪心\": greedy_coloring,\n",
+    "        \"AAE-MCP\": graph_coloring_v5,\n",
+    "        \"Greedy\": greedy_coloring,\n",
     "        \"Welsh-Powell\": welsh_powell_coloring,\n",
     "        \"DSATUR\": dsatur_coloring,\n",
     "    }\n",
@@ -591,19 +591,19 @@
      "text": [
       "\n",
       "各算法在不同实例上的着色数量:\n",
-      "           FunSearch-MCP  EoH-MCP  AAE-MCP  MEoH-MCP   贪心  Welsh-Powell  \\\n",
-      "MCP0500.5             68       65       65        72   72            71   \n",
-      "MCP1000.9            316      299      299       321  321           313   \n",
-      "MCP0500.1             18       16       16        20   20            18   \n",
-      "MCP0250.1             12       10       10        13   13            11   \n",
-      "MCP0125.9             53       51       51        56   56            53   \n",
-      "MCP0250.5             40       37       37        43   43            41   \n",
-      "MCP0125.5             24       22       22        26   26            23   \n",
-      "MCP0250.9             92       92       92        99   99            93   \n",
-      "MCP0125.1              7        6        6         8    8             7   \n",
-      "MCP1000.1             29       27       27        31   31            29   \n",
-      "MCP0500.9            171      170      170       175  175           169   \n",
-      "MCP1000.5            123      115      115       127  127           121   \n",
+      "           FunSearch-MCP  EoH-MCP  MEoH-MCP  AAE-MCP  Greedy  Welsh-Powell  \\\n",
+      "MCP0500.5             68       65        72       65      72            71   \n",
+      "MCP1000.9            316      299       321      299     321           313   \n",
+      "MCP0500.1             18       16        20       16      20            18   \n",
+      "MCP0250.1             12       10        13       10      13            11   \n",
+      "MCP0125.9             53       51        56       51      56            53   \n",
+      "MCP0250.5             40       37        43       37      43            41   \n",
+      "MCP0125.5             24       22        26       22      26            23   \n",
+      "MCP0250.9             92       92        99       92      99            93   \n",
+      "MCP0125.1              7        6         8        6       8             7   \n",
+      "MCP1000.1             29       27        31       27      31            29   \n",
+      "MCP0500.9            171      170       175      170     175           169   \n",
+      "MCP1000.5            123      115       127      115     127           121   \n",
       "\n",
       "           DSATUR  \n",
       "MCP0500.5      65  \n",
@@ -620,33 +620,33 @@
       "MCP1000.5     115  \n",
       "\n",
       "各算法在不同实例上的运行时间(秒):\n",
-      "           FunSearch-MCP   EoH-MCP  AAE-MCP  MEoH-MCP      贪心  Welsh-Powell  \\\n",
-      "MCP0500.5         0.0531   17.5173   0.2342    0.0772  0.0384        0.0647   \n",
-      "MCP1000.9         0.1921  141.4497   0.7749    1.1940  0.1230        0.5992   \n",
-      "MCP0500.1         0.0273    9.1615   0.0434    0.0063  0.0208        0.0190   \n",
-      "MCP0250.1         0.0108    1.9122   0.0242    0.0047  0.0098        0.0086   \n",
-      "MCP0125.9         0.0037    0.3753   0.0160    0.0116  0.0023        0.0068   \n",
-      "MCP0250.5         0.0111    2.3817   0.0539    0.0163  0.0107        0.0159   \n",
-      "MCP0125.5         0.0037    0.3252   0.0094    0.0037  0.0022        0.0035   \n",
-      "MCP0250.9         0.0138    2.7876   0.0882    0.0623  0.0098        0.0273   \n",
-      "MCP0125.1         0.0032    0.2459   0.0061    0.0006  0.0022        0.0017   \n",
-      "MCP1000.1         0.1838   80.1908   0.1365    0.0256  0.0782        0.0820   \n",
-      "MCP0500.9         0.0550   21.5202   0.1652    0.2121  0.0248        0.0891   \n",
-      "MCP1000.5         0.1247  122.0818   0.9329    0.4898  0.1717        0.3686   \n",
+      "           FunSearch-MCP   EoH-MCP  MEoH-MCP  AAE-MCP  Greedy  Welsh-Powell  \\\n",
+      "MCP0500.5         0.0579   18.2027    0.0938   0.2781  0.0417        0.0708   \n",
+      "MCP1000.9         0.2167  122.6014    1.1258   0.6846  0.0872        0.4910   \n",
+      "MCP0500.1         0.0271    8.2985    0.0060   0.0395  0.0208        0.0193   \n",
+      "MCP0250.1         0.0059    0.9747    0.0015   0.0082  0.0048        0.0041   \n",
+      "MCP0125.9         0.0018    0.1796    0.0047   0.0083  0.0015        0.0027   \n",
+      "MCP0250.5         0.0062    1.2001    0.0080   0.0207  0.0052        0.0065   \n",
+      "MCP0125.5         0.0016    0.1555    0.0018   0.0051  0.0014        0.0013   \n",
+      "MCP0250.9         0.0065    1.4176    0.0281   0.0361  0.0054        0.0130   \n",
+      "MCP0125.1         0.0016    0.2009    0.0006   0.0059  0.0028        0.0022   \n",
+      "MCP1000.1         0.1945   67.5939    0.0318   0.1373  0.0780        0.0838   \n",
+      "MCP0500.9         0.0266   11.5300    0.1568   0.1534  0.0220        0.0806   \n",
+      "MCP1000.5         0.1027   86.2889    0.2535   0.3925  0.0824        0.1860   \n",
       "\n",
       "            DSATUR  \n",
-      "MCP0500.5  12.9052  \n",
-      "MCP1000.9  62.9649  \n",
-      "MCP0500.1   8.4256  \n",
-      "MCP0250.1   1.6975  \n",
-      "MCP0125.9   0.2167  \n",
-      "MCP0250.5   1.7535  \n",
-      "MCP0125.5   0.2311  \n",
-      "MCP0250.9   1.9282  \n",
-      "MCP0125.1   0.2033  \n",
-      "MCP1000.1  67.1028  \n",
-      "MCP0500.9   9.3176  \n",
-      "MCP1000.5  69.0443  \n"
+      "MCP0500.5  13.6344  \n",
+      "MCP1000.9  61.6497  \n",
+      "MCP0500.1   7.5141  \n",
+      "MCP0250.1   0.8288  \n",
+      "MCP0125.9   0.1214  \n",
+      "MCP0250.5   0.9142  \n",
+      "MCP0125.5   0.1308  \n",
+      "MCP0250.9   0.9777  \n",
+      "MCP0125.1   0.2098  \n",
+      "MCP1000.1  57.1171  \n",
+      "MCP0500.9   7.5806  \n",
+      "MCP1000.5  62.1337  \n"
      ]
     }
    ],
@@ -686,18 +686,445 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n"
+     ]
+    },
     {
      "data": {
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",
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",
       "text/plain": [
-       "<Figure size 1000x600 with 1 Axes>"
+       "<Figure size 800x600 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "图片尺寸: 2400 x 1800 像素\n",
+      "FunSearch: (0.05, 79.42)\n",
+      "EoH: (26.55, 75.83)\n",
+      "MEoH: (0.14, 82.58)\n",
+      "AAE: (0.15, 75.83)\n",
+      "Greedy: (0.03, 82.58)\n",
+      "Welsh-Powell: (0.08, 79.08)\n",
+      "DSATUR: (17.73, 75.83)\n"
+     ]
     }
    ],
    "source": [
@@ -705,12 +1132,12 @@
     "avg_colors = df_colors.mean()\n",
     "avg_times = df_time.mean()\n",
     "\n",
-    "# 中文显示\n",
-    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
-    "plt.rcParams['axes.unicode_minus'] = False\n",
+    "# # 中文显示\n",
+    "# plt.rcParams['font.sans-serif'] = ['SimHei']\n",
+    "# plt.rcParams['axes.unicode_minus'] = False\n",
     "\n",
     "# 创建散点图\n",
-    "plt.figure(figsize=(10, 6))\n",
+    "plt.figure(figsize=(8, 6))\n",
     "\n",
     "# 设置坐标轴范围\n",
     "x_max = max(avg_times) * 1.05  # 扩大20%\n",
@@ -729,17 +1156,23 @@
     "    x = avg_times[alg]\n",
     "    y = avg_colors[alg]\n",
     "    # 替换算法名称\n",
-    "    display_name = alg.replace('EoH-MCP', 'EoH-GCP').replace('FunSearch-MCP', 'FunSearch-GCP').replace('AAE-MCP', 'AAE-GCP')\n",
+    "    display_name = alg.replace('EoH-MCP', 'EoH').replace('FunSearch-MCP', 'FunSearch').replace('AAE-MCP', 'AAE').replace('MEoH-MCP', 'MEoH')\n",
     "    plt.scatter(x, y,\n",
     "               color=colors[i % len(colors)], # 使用取模确保不会越界\n",
     "               marker=markers[i % len(markers)],\n",
     "               s=100,\n",
     "               label=display_name)\n",
     "    # 为DA和EOH设置不同的标注位置\n",
-    "    if alg in ['DSATUR', 'EoH-MCP']:\n",
+    "    if alg in ['DSATUR']:\n",
     "        xytext = (-90, 20)  # 左上方偏移\n",
+    "    elif alg in ['EoH-MCP']:\n",
+    "        xytext = (20, 20)\n",
+    "    elif alg in ['Greedy']:\n",
+    "        xytext = (0, -20)\n",
+    "    elif alg in ['MEoH-MCP']:\n",
+    "        xytext = (0, 20)\n",
     "    elif alg in ['FunSearch-MCP']:\n",
-    "        xytext = (-50, 20)\n",
+    "        xytext = (-40, 20)\n",
     "    else:\n",
     "        xytext = (20, -5)  # 右上方偏移\n",
     "        \n",
@@ -750,8 +1183,8 @@
     "                fontsize=18,\n",
     "                bbox=dict(facecolor='white', edgecolor='none', alpha=0.7))\n",
     "\n",
-    "plt.xlabel('平均运行时间(秒)', fontsize=18)\n",
-    "plt.ylabel('平均着色数量', fontsize=18)\n",
+    "plt.xlabel('Average running time (seconds)', fontsize=18)\n",
+    "plt.ylabel('Average color number', fontsize=18)\n",
     "\n",
     "# 设置刻度字体大小\n",
     "plt.xticks(fontsize=14)\n",
@@ -762,7 +1195,29 @@
     "\n",
     "plt.tight_layout()\n",
     "plt.savefig('mcppareto.png',dpi=300)\n",
-    "plt.show()"
+    "plt.show()\n",
+    "\n",
+    "# 输出这张图片的精准大小\n",
+    "import os\n",
+    "import matplotlib.pyplot as plt\n",
+    "from PIL import Image\n",
+    "# 打开图片\n",
+    "image_path = 'mcppareto.png'\n",
+    "image = Image.open(image_path)\n",
+    "# 获取图片的尺寸\n",
+    "width, height = image.size\n",
+    "# 输出图片的尺寸\n",
+    "print(f\"图片尺寸: {width} x {height} 像素\")\n",
+    "# 关闭图片\n",
+    "image.close()\n",
+    "\n",
+    "# 输出上面绘图中每个散点的名称以及两个分别的指标值\n",
+    "for i, alg in enumerate(avg_colors.index):\n",
+    "    x = avg_times[alg]\n",
+    "    y = avg_colors[alg]\n",
+    "    # 替换算法名称\n",
+    "    display_name = alg.replace('EoH-MCP', 'EoH').replace('FunSearch-MCP', 'FunSearch').replace('AAE-MCP', 'AAE').replace('MEoH-MCP', 'MEoH')\n",
+    "    print(f\"{display_name}: ({x:.2f}, {y:.2f})\")"
    ]
   },
   {
diff --git a/src/lead/problems/bp/dataset/data_loader.py b/src/lead/problems/bp/dataset/data_loader.py
index 175d8b2..a71a226 100644
--- a/src/lead/problems/bp/dataset/data_loader.py
+++ b/src/lead/problems/bp/dataset/data_loader.py
@@ -1,29 +1,26 @@
 import numpy as np
-import random
-from typing import List, Tuple, Dict
+from typing import Dict, List, Tuple
 
-def generate_dataset(num_items: int, container_size: Tuple[int, int], seed: int = 2025) -> Dict[str, Tuple[List[Tuple[int, int]], Tuple[int, int]]]:
+def generate_instance() -> Dict[str, Tuple[List[Tuple[int, int]], Tuple[int, int]]]:
     """
-    生成二维装箱问题的数据集
-
-    Args:
-        num_items: 物品数量
-        container_size: 容器的宽度和高度
-        seed: 随机种子，默认为2025
+    Generate a single instance for the 2D Bin Packing Problem.
 
     Returns:
-        Dict[str, Tuple[List[Tuple[int, int]], Tuple[int, int]]]: 包含物品列表和容器尺寸的字典
+        A dictionary containing:
+        - 'items': A list of tuples, where each tuple represents the (width, height) of an item.
+        - 'bin_dimensions': A tuple representing the (width, height) of the bin.
     """
-    random.seed(seed)
-    np.random.seed(seed)
+    np.random.seed(2025)  # Set seed for reproducibility
 
-    items = []
-    for _ in range(num_items):
-        width = random.randint(1, container_size[0] // 2)
-        height = random.randint(1, container_size[1] // 2)
-        items.append((width, height))
+    # Generate random item dimensions, ensuring no item exceeds the bin dimensions
+    bin_width, bin_height = 100, 100
+    n_items = 100
+    item_widths = np.random.randint(10, bin_width - 10, size=n_items)
+    item_heights = np.random.randint(10, bin_height - 10, size=n_items)
+    items = list(zip(item_widths, item_heights))
+    bin_dimensions = (bin_width, bin_height)
 
-    return {"data": (items, container_size)}
+    return {"items": items, "bin_dimensions": bin_dimensions}
 
 class ProblemDataLoader:
     def __init__(self, problem_path: str):
@@ -31,12 +28,11 @@ class ProblemDataLoader:
 
     def get_data(self) -> Dict[str, Tuple[List[Tuple[int, int]], Tuple[int, int]]]:
         """
-        加载二维装箱问题的数据集
+        Load the 2D Bin Packing Problem dataset.
 
         Returns:
-            Dict[str, Tuple[List[Tuple[int, int]], Tuple[int, int]]]: 包含物品列表和容器尺寸的字典
+            A dictionary containing:
+            - 'items': A list of tuples, where each tuple represents the (width, height) of an item.
+            - 'bin_dimensions': A tuple representing the (width, height) of the bin.
         """
-        # 使用固定随机种子生成数据集
-        num_items = 10
-        container_size = (100, 100)
-        return generate_dataset(num_items, container_size, seed=2025)
\ No newline at end of file
+        return generate_instance()
\ No newline at end of file
diff --git a/src/lead/problems/bp/evaluation.py b/src/lead/problems/bp/evaluation.py
index 2f657b8..bcaca2b 100644
--- a/src/lead/problems/bp/evaluation.py
+++ b/src/lead/problems/bp/evaluation.py
@@ -2,99 +2,87 @@ import numpy as np
 import time
 from typing import Callable, Dict, List, Tuple
 
-def evaluate(packing_func: Callable[[Dict[str, Tuple[List[Tuple[int, int]], Tuple[int, int]]]], List[Dict[str, int]]], 
+def evaluate(packing_func: Callable[[Dict[str, Tuple[List[Tuple[int, int]], Tuple[int, int]]]], List[List[Tuple[Tuple[int, int], Tuple[int, int]]]]], 
              input_data: Dict[str, Tuple[List[Tuple[int, int]], Tuple[int, int]]]) -> Dict[str, float]:
-    """评估二维装箱算法的多目标性能
+    """
+    Evaluate the performance of a 2D bin packing algorithm.
 
     Args:
-        packing_func: 装箱算法函数
-        input_data: 一个字典，包含两个部分:
-            - 'data': 一个元组，包含物品列表和容器尺寸
+        packing_func: The bin packing algorithm function.
+        input_data: A dictionary containing:
+            - 'items': A list of tuples, where each tuple represents the (width, height) of an item.
+            - 'bin_dimensions': A tuple representing the (width, height) of the bin.
 
     Returns:
-        Dict[str, float]: 包含两个目标值的字典:
-            - vacancy_rate: 容器的利用率
-            - execution_time: 运行时间(秒)
-            如果解不合法(物品超出容器边界或重叠)则返回无穷大
+        Dict[str, float]: A dictionary containing:
+            - bins_used: The number of bins used.
+            - execution_time: The execution time in seconds.
+            If the solution is invalid (e.g., items overlap or exceed bin boundaries), returns infinity for both metrics.
     """
     try:
-        # 解包输入数据
-        items, container = input_data["data"]
+        # Extract items and bin dimensions from input_data
+        items = input_data["items"]
+        bin_dimensions = input_data["bin_dimensions"]
 
-        # 计时并执行装箱算法
+        # Measure execution time
         start_time = time.time()
-        packing_result = packing_func(input_data)
-        print(f"[DEBUG] Packing result: {packing_result}")
+        bins = packing_func(input_data)
+        print(f"[DEBUG] Raw bins returned from packing_func: {bins}")
         end_time = time.time()
         execution_time = end_time - start_time
 
-        # 检查解的合法性
-        container_width, container_height = container
-        occupied_area = 0
+        # Validate the solution
+        bin_width, bin_height = bin_dimensions
+        total_bins_used = len(bins)
 
-        # 尝试标准化 packing_result 的结构
-        standardized_result = []
-        for placement in packing_result:
-            if isinstance(placement, tuple) and len(placement) >= 3:
-                x, y, rotated = placement[:3]
-                standardized_result.append({"x": x, "y": y, "rotated": rotated})
-            elif isinstance(placement, dict):
-                standardized_result.append(placement)
-            else:
-                print(f"[ERROR] Invalid packing_result structure: {packing_result}")
-                return {
-                    "vacancy_rate": float('inf'),
-                    "execution_time": float('inf')
-                }
-        packing_result = standardized_result
+        for bin_content in bins:
+            occupied_area = 0
+            for item in bin_content:
+                corner = item["corner"]
+                width, height = item["dimensions"]
+                x, y = corner
 
-        for item, placement in zip(items, packing_result):
-            item_width, item_height = item
-            x, y, rotated = placement["x"], placement["y"], placement["rotated"]
-
-            if rotated:
-                item_width, item_height = item_height, item_width
-
-            # 检查是否超出容器边界
-            if x + item_width > container_width or y + item_height > container_height:
-                print(f"非法解:物品超出容器边界")
-                return {
-                    "vacancy_rate": float('inf'),
-                    "execution_time": float('inf')
-                }
-
-            # 检查是否重叠
-            for other_item, other_placement in zip(items, packing_result):
-                if placement == other_placement:
-                    continue
-                other_x, other_y, other_rotated = other_placement["x"], other_placement["y"], other_placement["rotated"]
-                other_width, other_height = other_item
-                if other_rotated:
-                    other_width, other_height = other_height, other_width
-
-                if not (x + item_width <= other_x or other_x + other_width <= x or
-                        y + item_height <= other_y or other_y + other_height <= y):
-                    print(f"非法解:物品重叠")
+                # Check if the item exceeds bin boundaries
+                if x + width > bin_width or y + height > bin_height:
+                    print(f"Invalid solution: Item at ({x}, {y}) with size ({width}, {height}) exceeds bin boundaries.")
                     return {
-                        "vacancy_rate": float('inf'),
+                        "bins_used": float('inf'),
                         "execution_time": float('inf')
                     }
 
-            occupied_area += item_width * item_height
+                # Check for overlaps with other items in the same bin
+                for other_corner, (other_width, other_height) in bin_content:
+                    if (corner == other_corner):
+                        continue
+                    other_x, other_y = other_corner
+                    if not (x + width <= other_x or other_x + other_width <= x or
+                            y + height <= other_y or other_y + other_height <= y):
+                        print(f"Invalid solution: Items at ({x}, {y}) and ({other_x}, {other_y}) overlap.")
+                        return {
+                            "bins_used": float('inf'),
+                            "execution_time": float('inf')
+                        }
 
-        # 计算容器利用率
-        vacancy_rate = 1 - (occupied_area / (container_width * container_height))
+                occupied_area += width * height
 
-        print(f"执行时间:{execution_time:.4f}秒, 容器空置率:{vacancy_rate:.4f}")
+            # Ensure no item exceeds the bin's capacity
+            if occupied_area > bin_width * bin_height:
+                print(f"Invalid solution: Bin capacity exceeded.")
+                return {
+                    "bins_used": float('inf'),
+                    "execution_time": float('inf')
+                }
+
+        print(f"Execution time: {execution_time:.4f} seconds, Bins used: {total_bins_used}")
 
         return {
-            "vacancy_rate": vacancy_rate,
+            "bins_used": total_bins_used,
             "execution_time": execution_time
         }
 
     except Exception as e:
-        print(f"评估过程出错: {str(e)}")
+        print(f"Error during evaluation: {str(e)}")
         return {
-            "vacancy_rate": float('inf'),
+            "bins_used": float('inf'),
             "execution_time": float('inf')
         }
\ No newline at end of file
diff --git a/src/lead/problems/bp/multi_objective_evolution.log b/src/lead/problems/bp/multi_objective_evolution.log
index b639f6d..64dbccd 100644
--- a/src/lead/problems/bp/multi_objective_evolution.log
+++ b/src/lead/problems/bp/multi_objective_evolution.log
@@ -7,3 +7,12 @@ Generation 0004 | Pareto Front Size: 1 | Timestamp: 2025-05-13T15:56:18.905940
 Generation 0005 | Pareto Front Size: 1 | Timestamp: 2025-05-13T15:59:55.953455
 Generation 0006 | Pareto Front Size: 1 | Timestamp: 2025-05-13T16:00:39.951690
 Generation 0007 | Pareto Front Size: 1 | Timestamp: 2025-05-13T16:02:14.607527
+Generation 0000 | Pareto Front Size: 2 | Timestamp: 2025-05-15T15:47:17.387937
+Generation 0000 | Pareto Front Size: 1 | Timestamp: 2025-05-15T15:50:11.979996
+Generation 0001 | Pareto Front Size: 1 | Timestamp: 2025-05-15T15:52:01.064112
+Generation 0002 | Pareto Front Size: 1 | Timestamp: 2025-05-15T15:53:46.976949
+Generation 0003 | Pareto Front Size: 1 | Timestamp: 2025-05-15T15:55:05.807839
+Generation 0004 | Pareto Front Size: 1 | Timestamp: 2025-05-15T15:56:30.922968
+Generation 0005 | Pareto Front Size: 1 | Timestamp: 2025-05-15T16:00:15.734229
+Generation 0006 | Pareto Front Size: 1 | Timestamp: 2025-05-15T16:01:31.540137
+Generation 0007 | Pareto Front Size: 1 | Timestamp: 2025-05-15T16:05:09.684054
diff --git a/src/lead/problems/bp/problem_config.json b/src/lead/problems/bp/problem_config.json
index c80058b..d0eb827 100644
--- a/src/lead/problems/bp/problem_config.json
+++ b/src/lead/problems/bp/problem_config.json
@@ -1,10 +1,10 @@
 {
-    "description": "尝试开发一个高效的算法用于解决二维装箱问题。你被给定了一组矩形物品和一个固定大小的矩形容器，目标是通过算法的规划将所有物品放入容器中，使得容器的利用率最大化。",
+    "description": "开发一个高效的算法用于解决二维装箱问题。给定一组矩形物品和一个固定大小的矩形容器，目标是通过算法规划将所有物品放入尽可能少的容器中。",
     "function_name": "solve_bp",
-    "input_format": "一个字典，包含两个部分：\n1. 'data': 一个元组，包含多个矩形物品的列表和一个表示容器宽度和高度的元组。\n   - 矩形物品列表的每个元素是一个元组，表示物品的宽度和高度。\n   - 容器元组表示容器的宽度和高度。\n",
-    "output_format": "返回一个列表，表示每个物品在容器中的位置和旋转状态。\n每个元素是一个字典，包含以下键：\n1. 'x': 物品左上角的x坐标。\n2. 'y': 物品左上角的y坐标。\n3. 'rotated': 一个布尔值，表示物品是否旋转。",
+    "input_format": "一个字典，包含以下两部分：\n1. 'items': 一个列表，包含多个矩形物品的尺寸，每个物品由其宽度和高度表示为一个元组 (width, height)。\n2. 'bin_dimensions': 一个元组，表示容器的宽度和高度 (width, height)。",
+    "output_format": "返回一个列表，表示每个容器中的物品放置情况。\n每个容器是一个列表，包含多个物品的放置信息，每个物品由以下两部分组成：\n1. corner: 一个元组，表示物品左上角的坐标 (x, y)。\n2. dimensions: 一个元组，表示物品的宽度和高度 (width, height)。",
     "multi_objective": true,
-    "objective_names": ["vacancy_rate", "execution_time"],
+    "objective_names": ["bins_used", "execution_time"],
     "evaluation_timeout": 60,
     "llm_config": {
         "api_key": "sk-cOqgMkQ605Om9Z28q3UtAfOAtOn7c53tld94Cu01oOEoVTmg",
@@ -16,7 +16,7 @@
     "evolution_params": {
         "algorithm": "MO",
         "population_size": 2,
-        "generations": 8,
+        "generations": 2,
         "mutation_rate": 0.5,
         "crossover_rate": 0.4,
         "F": 0.8,
diff --git a/src/lead/utils/multi_objective/evaluator.py b/src/lead/utils/multi_objective/evaluator.py
index 1be493f..cc22d06 100644
--- a/src/lead/utils/multi_objective/evaluator.py
+++ b/src/lead/utils/multi_objective/evaluator.py
@@ -39,6 +39,7 @@ class MultiObjectiveEvaluator:
             
             # 使用超时控制调用评估函数
             timeout = Timeout(self.timeout)
+            # print(f"[DEBUG] Dataset structure: {self.dataset}")
             if self.dataset is not None:
                 results = timeout.run(self.evaluation_module.evaluate, func, self.dataset)
             else:
diff --git a/tsp_data/tsp_pareto.png b/tsp_data/tsp_pareto.png
new file mode 100644
index 0000000..c93bcc4
Binary files /dev/null and b/tsp_data/tsp_pareto.png differ
diff --git a/tsp_data/tsp_test.ipynb b/tsp_data/tsp_test.ipynb
index 6e370cb..06c11d5 100644
--- a/tsp_data/tsp_test.ipynb
+++ b/tsp_data/tsp_test.ipynb
@@ -223,22 +223,22 @@
       "测试实例: burma14.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0001秒, 路径长度:38.69\n",
+      "执行时间:0.0000秒, 路径长度:38.69\n",
       "\n",
       "使用算法: 最近邻算法\n",
       "执行时间:0.0000秒, 路径长度:38.69\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0010秒, 路径长度:32.44\n",
+      "执行时间:0.0004秒, 路径长度:32.44\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0136秒, 路径长度:38.69\n",
+      "执行时间:0.0120秒, 路径长度:38.69\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.0212秒, 路径长度:30.88\n",
+      "执行时间:0.0206秒, 路径长度:31.23\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0010秒, 路径长度:38.80\n",
+      "执行时间:0.0013秒, 路径长度:38.80\n",
       "\n",
       "测试实例: ulysses16.tsp\n",
       "\n",
@@ -249,33 +249,33 @@
       "执行时间:0.0000秒, 路径长度:104.73\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0004秒, 路径长度:79.39\n",
+      "执行时间:0.0007秒, 路径长度:79.39\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0113秒, 路径长度:88.25\n",
+      "执行时间:0.0099秒, 路径长度:76.87\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.0254秒, 路径长度:74.20\n",
+      "执行时间:0.0241秒, 路径长度:73.99\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0012秒, 路径长度:104.65\n",
+      "执行时间:0.0009秒, 路径长度:104.65\n",
       "\n",
       "测试实例: ulysses22.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0001秒, 路径长度:89.64\n",
+      "执行时间:0.0000秒, 路径长度:89.64\n",
       "\n",
       "使用算法: 最近邻算法\n",
       "执行时间:0.0001秒, 路径长度:89.64\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0011秒, 路径长度:76.99\n",
+      "执行时间:0.0010秒, 路径长度:76.99\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0144秒, 路径长度:82.21\n",
+      "执行时间:0.0160秒, 路径长度:89.64\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.0340秒, 路径长度:76.13\n",
+      "执行时间:0.0349秒, 路径长度:76.89\n",
       "\n",
       "使用算法: MEoH-TSP\n",
       "执行时间:0.0012秒, 路径长度:91.92\n",
@@ -306,59 +306,59 @@
       "执行时间:0.0003秒, 路径长度:40526.42\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0003秒, 路径长度:40526.42\n",
+      "执行时间:0.0002秒, 路径长度:40526.42\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0112秒, 路径长度:37314.09\n",
+      "执行时间:0.0124秒, 路径长度:37314.09\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0363秒, 路径长度:40526.42\n",
+      "执行时间:0.0307秒, 路径长度:40526.42\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.0693秒, 路径长度:35594.44\n",
+      "执行时间:0.0671秒, 路径长度:35738.05\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0033秒, 路径长度:37686.87\n",
+      "执行时间:0.0029秒, 路径长度:37686.87\n",
       "\n",
       "测试实例: eil51.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0004秒, 路径长度:513.61\n",
+      "执行时间:0.0005秒, 路径长度:513.61\n",
       "\n",
       "使用算法: 最近邻算法\n",
       "执行时间:0.0004秒, 路径长度:513.61\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0150秒, 路径长度:496.25\n",
+      "执行时间:0.0146秒, 路径长度:496.25\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0373秒, 路径长度:513.61\n",
+      "执行时间:0.0342秒, 路径长度:513.61\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.0755秒, 路径长度:465.91\n",
+      "执行时间:0.0815秒, 路径长度:465.91\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0032秒, 路径长度:458.95\n",
+      "执行时间:0.0030秒, 路径长度:458.95\n",
       "\n",
       "测试实例: berlin52.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0003秒, 路径长度:8980.92\n",
+      "执行时间:0.0004秒, 路径长度:8980.92\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0005秒, 路径长度:8980.92\n",
+      "执行时间:0.0002秒, 路径长度:8980.92\n",
       "\n",
       "使用算法: 插入法\n",
       "执行时间:0.0169秒, 路径长度:9014.89\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0456秒, 路径长度:8980.92\n",
+      "执行时间:0.0442秒, 路径长度:8980.92\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.0881秒, 路径长度:8383.59\n",
+      "执行时间:0.0888秒, 路径长度:8178.40\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0030秒, 路径长度:8835.06\n",
+      "执行时间:0.0040秒, 路径长度:8835.06\n",
       "\n",
       "测试实例: st70.tsp\n",
       "\n",
@@ -366,139 +366,139 @@
       "执行时间:0.0006秒, 路径长度:805.53\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0005秒, 路径长度:805.53\n",
+      "执行时间:0.0006秒, 路径长度:805.53\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0393秒, 路径长度:778.99\n",
+      "执行时间:0.0399秒, 路径长度:778.99\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0635秒, 路径长度:800.35\n",
+      "执行时间:0.0584秒, 路径长度:805.53\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1139秒, 路径长度:753.15\n",
+      "执行时间:0.1202秒, 路径长度:753.15\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0036秒, 路径长度:871.65\n",
+      "执行时间:0.0047秒, 路径长度:871.65\n",
       "\n",
       "测试实例: pr76.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0003秒, 路径长度:153461.92\n",
+      "执行时间:0.0008秒, 路径长度:153461.92\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0003秒, 路径长度:153461.92\n",
+      "执行时间:0.0007秒, 路径长度:153461.92\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0463秒, 路径长度:125936.21\n",
+      "执行时间:0.0511秒, 路径长度:125936.21\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0707秒, 路径长度:141744.29\n",
+      "执行时间:0.0688秒, 路径长度:140565.41\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1455秒, 路径长度:113661.65\n",
+      "执行时间:0.1371秒, 路径长度:117831.22\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0047秒, 路径长度:123787.14\n",
+      "执行时间:0.0046秒, 路径长度:123787.14\n",
       "\n",
       "测试实例: eil76.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0008秒, 路径长度:711.99\n",
+      "执行时间:0.0009秒, 路径长度:711.99\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0006秒, 路径长度:711.99\n",
+      "执行时间:0.0007秒, 路径长度:711.99\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0473秒, 路径长度:612.39\n",
+      "执行时间:0.0430秒, 路径长度:612.39\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0599秒, 路径长度:669.24\n",
+      "执行时间:0.0673秒, 路径长度:669.24\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1086秒, 路径长度:622.71\n",
+      "执行时间:0.1221秒, 路径长度:622.71\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0040秒, 路径长度:577.27\n",
+      "执行时间:0.0046秒, 路径长度:577.27\n",
       "\n",
       "测试实例: gr96.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0010秒, 路径长度:707.09\n",
-      "\n",
-      "使用算法: 最近邻算法\n",
       "执行时间:0.0009秒, 路径长度:707.09\n",
       "\n",
+      "使用算法: 最近邻算法\n",
+      "执行时间:0.0011秒, 路径长度:707.09\n",
+      "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0832秒, 路径长度:651.44\n",
+      "执行时间:0.0923秒, 路径长度:651.44\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0823秒, 路径长度:707.09\n",
+      "执行时间:0.0769秒, 路径长度:707.09\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.2177秒, 路径长度:623.53\n",
+      "执行时间:0.2633秒, 路径长度:623.53\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0063秒, 路径长度:573.48\n",
+      "执行时间:0.0065秒, 路径长度:573.48\n",
       "\n",
       "测试实例: rat99.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0011秒, 路径长度:1564.72\n",
+      "执行时间:0.0013秒, 路径长度:1564.72\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0007秒, 路径长度:1564.72\n",
+      "执行时间:0.0011秒, 路径长度:1564.72\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0929秒, 路径长度:1482.02\n",
+      "执行时间:0.1136秒, 路径长度:1482.02\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0926秒, 路径长度:1564.72\n",
+      "执行时间:0.1031秒, 路径长度:1564.72\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1861秒, 路径长度:1377.07\n",
+      "执行时间:0.1965秒, 路径长度:1377.07\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0046秒, 路径长度:1492.74\n",
+      "执行时间:0.0057秒, 路径长度:1492.74\n",
       "\n",
       "测试实例: rd100.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0015秒, 路径长度:9941.16\n",
+      "执行时间:0.0005秒, 路径长度:9941.16\n",
       "\n",
       "使用算法: 最近邻算法\n",
       "执行时间:0.0012秒, 路径长度:9941.16\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0966秒, 路径长度:8979.37\n",
+      "执行时间:0.1072秒, 路径长度:8979.37\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0791秒, 路径长度:9941.16\n",
+      "执行时间:0.0986秒, 路径长度:9941.16\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1733秒, 路径长度:8864.57\n",
+      "执行时间:0.2223秒, 路径长度:8864.57\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0046秒, 路径长度:10510.18\n",
+      "执行时间:0.0058秒, 路径长度:10510.18\n",
       "\n",
       "测试实例: kroB100.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0009秒, 路径长度:29155.04\n",
+      "执行时间:0.0015秒, 路径长度:29155.04\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0012秒, 路径长度:29155.04\n",
+      "执行时间:0.0013秒, 路径长度:29155.04\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0981秒, 路径长度:25580.92\n",
+      "执行时间:0.1206秒, 路径长度:25580.92\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0874秒, 路径长度:29155.04\n",
+      "执行时间:0.0981秒, 路径长度:29155.04\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1947秒, 路径长度:25613.43\n",
+      "执行时间:0.2087秒, 路径长度:25392.46\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0046秒, 路径长度:25679.71\n",
+      "执行时间:0.0033秒, 路径长度:25679.71\n",
       "\n",
       "测试实例: kroD100.tsp\n",
       "\n",
@@ -506,19 +506,19 @@
       "执行时间:0.0012秒, 路径长度:26950.46\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0010秒, 路径长度:26950.46\n",
+      "执行时间:0.0007秒, 路径长度:26950.46\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.0972秒, 路径长度:25204.27\n",
+      "执行时间:0.1119秒, 路径长度:25204.27\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0952秒, 路径长度:26950.46\n",
+      "执行时间:0.0862秒, 路径长度:26950.46\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1958秒, 路径长度:24720.72\n",
+      "执行时间:0.1775秒, 路径长度:24565.25\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0036秒, 路径长度:26072.81\n",
+      "执行时间:0.0061秒, 路径长度:26072.81\n",
       "\n",
       "测试实例: kroA100.tsp\n",
       "\n",
@@ -529,36 +529,36 @@
       "执行时间:0.0010秒, 路径长度:26856.39\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.1088秒, 路径长度:24307.78\n",
+      "执行时间:0.0981秒, 路径长度:24307.78\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0976秒, 路径长度:26856.39\n",
+      "执行时间:0.0825秒, 路径长度:26856.39\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.2082秒, 路径长度:23078.70\n",
+      "执行时间:0.1498秒, 路径长度:22957.15\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0069秒, 路径长度:22683.29\n",
+      "执行时间:0.0061秒, 路径长度:22683.29\n",
       "\n",
       "测试实例: kroC100.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0010秒, 路径长度:26327.36\n",
-      "\n",
-      "使用算法: 最近邻算法\n",
       "执行时间:0.0012秒, 路径长度:26327.36\n",
       "\n",
+      "使用算法: 最近邻算法\n",
+      "执行时间:0.0015秒, 路径长度:26327.36\n",
+      "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.1006秒, 路径长度:25262.17\n",
+      "执行时间:0.0983秒, 路径长度:25262.17\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0923秒, 路径长度:26327.36\n",
+      "执行时间:0.0842秒, 路径长度:26327.36\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1707秒, 路径长度:23205.07\n",
+      "执行时间:0.1798秒, 路径长度:23253.25\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0060秒, 路径长度:24294.06\n",
+      "执行时间:0.0049秒, 路径长度:24294.06\n",
       "\n",
       "测试实例: kroE100.tsp\n",
       "\n",
@@ -566,19 +566,19 @@
       "执行时间:0.0011秒, 路径长度:27587.19\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0013秒, 路径长度:27587.19\n",
+      "执行时间:0.0008秒, 路径长度:27587.19\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.1067秒, 路径长度:25902.00\n",
+      "执行时间:0.1026秒, 路径长度:25902.00\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0917秒, 路径长度:27587.19\n",
+      "执行时间:0.0972秒, 路径长度:27587.19\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1582秒, 路径长度:24382.95\n",
+      "执行时间:0.1961秒, 路径长度:24382.95\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0053秒, 路径长度:25221.45\n",
+      "执行时间:0.0061秒, 路径长度:25221.45\n",
       "\n",
       "测试实例: eil101.tsp\n",
       "\n",
@@ -586,99 +586,99 @@
       "执行时间:0.0011秒, 路径长度:825.24\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0015秒, 路径长度:825.24\n",
+      "执行时间:0.0013秒, 路径长度:825.24\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.1047秒, 路径长度:702.96\n",
+      "执行时间:0.1086秒, 路径长度:702.96\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0899秒, 路径长度:847.59\n",
+      "执行时间:0.0867秒, 路径长度:847.59\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.2089秒, 路径长度:702.70\n",
+      "执行时间:0.2088秒, 路径长度:702.70\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0063秒, 路径长度:720.41\n",
+      "执行时间:0.0051秒, 路径长度:720.41\n",
       "\n",
       "测试实例: lin105.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0011秒, 路径长度:20362.76\n",
+      "执行时间:0.0014秒, 路径长度:20362.76\n",
       "\n",
       "使用算法: 最近邻算法\n",
       "执行时间:0.0012秒, 路径长度:20362.76\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.1178秒, 路径长度:16934.62\n",
+      "执行时间:0.1155秒, 路径长度:16934.62\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0933秒, 路径长度:20362.76\n",
+      "执行时间:0.0962秒, 路径长度:20362.76\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.2248秒, 路径长度:18092.45\n",
+      "执行时间:0.1928秒, 路径长度:18371.79\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0086秒, 路径长度:19041.58\n",
+      "执行时间:0.0026秒, 路径长度:19041.58\n",
       "\n",
       "测试实例: pr107.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0018秒, 路径长度:46678.15\n",
+      "执行时间:0.0016秒, 路径长度:46678.15\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0015秒, 路径长度:46678.15\n",
+      "执行时间:0.0014秒, 路径长度:46678.15\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.1222秒, 路径长度:52587.76\n",
+      "执行时间:0.1403秒, 路径长度:52587.76\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.0850秒, 路径长度:47029.63\n",
+      "执行时间:0.1044秒, 路径长度:47029.63\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1293秒, 路径长度:45487.66\n",
+      "执行时间:0.1547秒, 路径长度:44905.53\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0042秒, 路径长度:51115.61\n",
+      "执行时间:0.0060秒, 路径长度:51115.61\n",
       "\n",
       "测试实例: pr124.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0015秒, 路径长度:69299.43\n",
+      "执行时间:0.0017秒, 路径长度:69299.43\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0010秒, 路径长度:69299.43\n",
+      "执行时间:0.0015秒, 路径长度:69299.43\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.1867秒, 路径长度:65318.19\n",
+      "执行时间:0.2034秒, 路径长度:65318.19\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1198秒, 路径长度:69299.43\n",
+      "执行时间:0.1309秒, 路径长度:69299.43\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.2008秒, 路径长度:60665.35\n",
+      "执行时间:0.1921秒, 路径长度:63601.53\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0061秒, 路径长度:68371.30\n",
+      "执行时间:0.0054秒, 路径长度:68371.30\n",
       "\n",
       "测试实例: bier127.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0018秒, 路径长度:135751.78\n",
+      "执行时间:0.0015秒, 路径长度:135751.78\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0018秒, 路径长度:135751.78\n",
+      "执行时间:0.0016秒, 路径长度:135751.78\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.2051秒, 路径长度:140690.94\n",
+      "执行时间:0.2007秒, 路径长度:140690.94\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1205秒, 路径长度:135751.78\n",
+      "执行时间:0.1216秒, 路径长度:135751.78\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.2334秒, 路径长度:122761.77\n",
+      "执行时间:0.2196秒, 路径长度:123202.55\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0059秒, 路径长度:138054.23\n",
+      "执行时间:0.0069秒, 路径长度:138054.23\n",
       "\n",
       "测试实例: ch130.tsp\n",
       "\n",
@@ -686,359 +686,359 @@
       "执行时间:0.0017秒, 路径长度:7575.29\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0017秒, 路径长度:7575.29\n",
+      "执行时间:0.0020秒, 路径长度:7575.29\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.2264秒, 路径长度:7279.21\n",
+      "执行时间:0.2338秒, 路径长度:7279.21\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1234秒, 路径长度:7575.29\n",
+      "执行时间:0.1343秒, 路径长度:7575.29\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.2159秒, 路径长度:7093.18\n",
+      "执行时间:0.2306秒, 路径长度:7093.18\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0068秒, 路径长度:7091.76\n",
+      "执行时间:0.0070秒, 路径长度:7091.76\n",
       "\n",
       "测试实例: pr136.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0023秒, 路径长度:120777.86\n",
+      "执行时间:0.0020秒, 路径长度:120777.86\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0019秒, 路径长度:120777.86\n",
+      "执行时间:0.0014秒, 路径长度:120777.86\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.2532秒, 路径长度:109587.25\n",
+      "执行时间:0.2884秒, 路径长度:109587.25\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1206秒, 路径长度:118776.81\n",
+      "执行时间:0.1478秒, 路径长度:118776.81\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.2525秒, 路径长度:110107.30\n",
+      "执行时间:0.2450秒, 路径长度:110347.07\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0069秒, 路径长度:123247.21\n",
+      "执行时间:0.0074秒, 路径长度:123247.21\n",
       "\n",
       "测试实例: gr137.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0021秒, 路径长度:1022.22\n",
+      "执行时间:0.0024秒, 路径长度:1022.22\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0022秒, 路径长度:1022.22\n",
+      "执行时间:0.0017秒, 路径长度:1022.22\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.2709秒, 路径长度:821.29\n",
+      "执行时间:0.2412秒, 路径长度:821.29\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1346秒, 路径长度:1022.22\n",
+      "执行时间:0.1438秒, 路径长度:1022.22\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.4666秒, 路径长度:849.98\n",
+      "执行时间:0.5256秒, 路径长度:849.98\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0077秒, 路径长度:901.99\n",
+      "执行时间:0.0085秒, 路径长度:901.99\n",
       "\n",
       "测试实例: pr144.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0020秒, 路径长度:61650.72\n",
+      "执行时间:0.0025秒, 路径长度:61650.72\n",
       "\n",
       "使用算法: 最近邻算法\n",
       "执行时间:0.0021秒, 路径长度:61650.72\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.2869秒, 路径长度:73033.13\n",
+      "执行时间:0.3768秒, 路径长度:73033.13\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1331秒, 路径长度:61650.72\n",
+      "执行时间:0.1484秒, 路径长度:61650.72\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.1867秒, 路径长度:61399.21\n",
+      "执行时间:0.2336秒, 路径长度:61214.65\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0056秒, 路径长度:60133.16\n",
+      "执行时间:0.0070秒, 路径长度:60133.16\n",
       "\n",
       "测试实例: kroA150.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0019秒, 路径长度:33609.87\n",
+      "执行时间:0.0025秒, 路径长度:33609.87\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0022秒, 路径长度:33609.87\n",
+      "执行时间:0.0019秒, 路径长度:33609.87\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.3287秒, 路径长度:29966.54\n",
+      "执行时间:0.3564秒, 路径长度:29966.54\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1343秒, 路径长度:33609.87\n",
+      "执行时间:0.1586秒, 路径长度:33609.87\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.3946秒, 路径长度:28613.32\n",
+      "执行时间:0.4204秒, 路径长度:28767.65\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0073秒, 路径长度:31060.89\n",
+      "执行时间:0.0089秒, 路径长度:31060.89\n",
       "\n",
       "测试实例: ch150.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0020秒, 路径长度:8194.61\n",
+      "执行时间:0.0028秒, 路径长度:8194.61\n",
       "\n",
       "使用算法: 最近邻算法\n",
       "执行时间:0.0020秒, 路径长度:8194.61\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.3128秒, 路径长度:7994.29\n",
+      "执行时间:0.3516秒, 路径长度:7994.29\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1503秒, 路径长度:8194.61\n",
+      "执行时间:0.1501秒, 路径长度:8194.61\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.4033秒, 路径长度:7161.32\n",
+      "执行时间:0.3711秒, 路径长度:7161.32\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0069秒, 路径长度:7589.72\n",
+      "执行时间:0.0087秒, 路径长度:7589.72\n",
       "\n",
       "测试实例: kroB150.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0022秒, 路径长度:32825.75\n",
+      "执行时间:0.0020秒, 路径长度:32825.75\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0026秒, 路径长度:32825.75\n",
+      "执行时间:0.0024秒, 路径长度:32825.75\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.3337秒, 路径长度:31588.68\n",
+      "执行时间:0.3577秒, 路径长度:31588.68\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1425秒, 路径长度:32825.75\n",
+      "执行时间:0.1559秒, 路径长度:32825.75\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.4610秒, 路径长度:28339.58\n",
+      "执行时间:0.4201秒, 路径长度:28181.08\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0083秒, 路径长度:29848.14\n",
+      "执行时间:0.0090秒, 路径长度:29848.14\n",
       "\n",
       "测试实例: pr152.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0021秒, 路径长度:85702.95\n",
+      "执行时间:0.0025秒, 路径长度:85702.95\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0023秒, 路径长度:85702.95\n",
+      "执行时间:0.0022秒, 路径长度:85702.95\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.3738秒, 路径长度:88530.82\n",
+      "执行时间:0.3534秒, 路径长度:88530.82\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1372秒, 路径长度:85702.95\n",
+      "执行时间:0.1499秒, 路径长度:85702.95\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.3713秒, 路径长度:80000.73\n",
+      "执行时间:0.2910秒, 路径长度:80448.65\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0107秒, 路径长度:92682.12\n",
+      "执行时间:0.0070秒, 路径长度:92682.12\n",
       "\n",
       "测试实例: u159.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0023秒, 路径长度:54669.03\n",
+      "执行时间:0.0022秒, 路径长度:54669.03\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0026秒, 路径长度:54669.03\n",
+      "执行时间:0.0023秒, 路径长度:54669.03\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.4197秒, 路径长度:49981.41\n",
+      "执行时间:0.3635秒, 路径长度:49981.41\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.1548秒, 路径长度:57436.69\n",
+      "执行时间:0.1661秒, 路径长度:57436.69\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.3393秒, 路径长度:50463.07\n",
+      "执行时间:0.3241秒, 路径长度:50416.01\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0089秒, 路径长度:51577.24\n",
+      "执行时间:0.0079秒, 路径长度:51577.24\n",
       "\n",
       "测试实例: rat195.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0039秒, 路径长度:2761.96\n",
+      "执行时间:0.0036秒, 路径长度:2761.96\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0046秒, 路径长度:2761.96\n",
+      "执行时间:0.0037秒, 路径长度:2761.96\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.7990秒, 路径长度:2814.57\n",
+      "执行时间:0.8294秒, 路径长度:2814.57\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.2376秒, 路径长度:2761.96\n",
+      "执行时间:0.2163秒, 路径长度:2761.96\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.5750秒, 路径长度:2490.60\n",
+      "执行时间:0.5768秒, 路径长度:2490.60\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0107秒, 路径长度:2575.61\n",
+      "执行时间:0.0116秒, 路径长度:2575.61\n",
       "\n",
       "测试实例: d198.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0044秒, 路径长度:18620.07\n",
-      "\n",
-      "使用算法: 最近邻算法\n",
       "执行时间:0.0048秒, 路径长度:18620.07\n",
       "\n",
+      "使用算法: 最近邻算法\n",
+      "执行时间:0.0040秒, 路径长度:18620.07\n",
+      "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.7791秒, 路径长度:17631.80\n",
+      "执行时间:0.8395秒, 路径长度:17631.80\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.2144秒, 路径长度:18620.07\n",
+      "执行时间:0.2329秒, 路径长度:18605.19\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.5679秒, 路径长度:17340.94\n",
+      "执行时间:0.6631秒, 路径长度:17340.94\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0084秒, 路径长度:19454.99\n",
+      "执行时间:0.0113秒, 路径长度:19454.99\n",
       "\n",
       "测试实例: kroB200.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0036秒, 路径长度:36981.59\n",
+      "执行时间:0.0039秒, 路径长度:36981.59\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0037秒, 路径长度:36981.59\n",
+      "执行时间:0.0034秒, 路径长度:36981.59\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.8396秒, 路径长度:35421.70\n",
+      "执行时间:0.8084秒, 路径长度:35421.70\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.2561秒, 路径长度:36981.59\n",
+      "执行时间:0.2069秒, 路径长度:36981.59\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.6496秒, 路径长度:34175.92\n",
+      "执行时间:0.7495秒, 路径长度:34372.39\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0090秒, 路径长度:34079.08\n",
+      "执行时间:0.0099秒, 路径长度:34079.08\n",
       "\n",
       "测试实例: kroA200.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0043秒, 路径长度:35798.41\n",
+      "执行时间:0.0038秒, 路径长度:35798.41\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0037秒, 路径长度:35798.41\n",
+      "执行时间:0.0039秒, 路径长度:35798.41\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.8220秒, 路径长度:35337.51\n",
+      "执行时间:0.8769秒, 路径长度:35337.51\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.2057秒, 路径长度:35798.41\n",
+      "执行时间:0.2339秒, 路径长度:35798.41\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.9275秒, 路径长度:30478.90\n",
+      "执行时间:0.8138秒, 路径长度:30701.99\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0118秒, 路径长度:33224.38\n",
+      "执行时间:0.0106秒, 路径长度:33224.38\n",
       "\n",
       "测试实例: gr202.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0043秒, 路径长度:619.40\n",
+      "执行时间:0.0033秒, 路径长度:619.40\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0044秒, 路径长度:619.40\n",
+      "执行时间:0.0033秒, 路径长度:619.40\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:0.8180秒, 路径长度:570.14\n",
+      "执行时间:0.8244秒, 路径长度:570.14\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.2131秒, 路径长度:619.40\n",
+      "执行时间:0.2186秒, 路径长度:619.40\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.8817秒, 路径长度:529.30\n",
+      "执行时间:0.9231秒, 路径长度:529.30\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0115秒, 路径长度:559.57\n",
+      "执行时间:0.0095秒, 路径长度:559.57\n",
       "\n",
       "测试实例: tsp225.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0051秒, 路径长度:4829.00\n",
+      "执行时间:0.0040秒, 路径长度:4829.00\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0053秒, 路径长度:4829.00\n",
+      "执行时间:0.0047秒, 路径长度:4829.00\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:1.1301秒, 路径长度:4468.20\n",
+      "执行时间:1.2282秒, 路径长度:4468.20\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.2429秒, 路径长度:4786.42\n",
+      "执行时间:0.2567秒, 路径长度:4786.42\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:1.1539秒, 路径长度:4169.09\n",
+      "执行时间:1.2099秒, 路径长度:4169.09\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0096秒, 路径长度:4430.19\n",
+      "执行时间:0.0128秒, 路径长度:4430.19\n",
       "\n",
       "测试实例: ts225.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0057秒, 路径长度:152493.55\n",
+      "执行时间:0.0055秒, 路径长度:152493.55\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0037秒, 路径长度:152493.55\n",
+      "执行时间:0.0044秒, 路径长度:152493.55\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:1.0775秒, 路径长度:160009.16\n",
+      "执行时间:1.1208秒, 路径长度:160009.16\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.2497秒, 路径长度:146183.10\n",
+      "执行时间:0.2431秒, 路径长度:146183.10\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.7152秒, 路径长度:139697.02\n",
+      "执行时间:0.6736秒, 路径长度:139697.02\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0114秒, 路径长度:131162.09\n",
+      "执行时间:0.0116秒, 路径长度:131162.09\n",
       "\n",
       "测试实例: pr226.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0040秒, 路径长度:94685.45\n",
+      "执行时间:0.0047秒, 路径长度:94685.45\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0040秒, 路径长度:94685.45\n",
+      "执行时间:0.0038秒, 路径长度:94685.45\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:1.1298秒, 路径长度:91024.65\n",
+      "执行时间:1.1522秒, 路径长度:91024.65\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.2426秒, 路径长度:94402.09\n",
+      "执行时间:0.3356秒, 路径长度:94402.09\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.5740秒, 路径长度:87543.04\n",
+      "执行时间:0.5864秒, 路径长度:87543.04\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0107秒, 路径长度:96212.20\n",
+      "执行时间:0.0140秒, 路径长度:96212.20\n",
       "\n",
       "测试实例: gr229.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0048秒, 路径长度:2014.71\n",
+      "执行时间:0.0060秒, 路径长度:2014.71\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0047秒, 路径长度:2014.71\n",
+      "执行时间:0.0057秒, 路径长度:2014.71\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:1.1679秒, 路径长度:1825.83\n",
+      "执行时间:1.2088秒, 路径长度:1825.83\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.2532秒, 路径长度:2014.71\n",
+      "执行时间:0.2919秒, 路径长度:2014.71\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.9931秒, 路径长度:1764.18\n",
+      "执行时间:1.0688秒, 路径长度:1764.18\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0099秒, 路径长度:1987.56\n",
+      "执行时间:0.0159秒, 路径长度:1987.56\n",
       "\n",
       "测试实例: gil262.tsp\n",
       "\n",
@@ -1046,159 +1046,159 @@
       "执行时间:0.0067秒, 路径长度:3241.47\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0060秒, 路径长度:3241.47\n",
+      "执行时间:0.0070秒, 路径长度:3241.47\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:1.7432秒, 路径长度:2804.23\n",
+      "执行时间:1.8069秒, 路径长度:2804.23\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.3277秒, 路径长度:3259.42\n",
+      "执行时间:0.3174秒, 路径长度:3259.42\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:1.8501秒, 路径长度:2757.03\n",
+      "执行时间:1.6125秒, 路径长度:2757.03\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0154秒, 路径长度:2748.90\n",
+      "执行时间:0.0139秒, 路径长度:2748.90\n",
       "\n",
       "测试实例: pr264.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0071秒, 路径长度:58022.86\n",
+      "执行时间:0.0072秒, 路径长度:58022.86\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0069秒, 路径长度:58022.86\n",
+      "执行时间:0.0068秒, 路径长度:58022.86\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:1.8694秒, 路径长度:58225.34\n",
+      "执行时间:1.9408秒, 路径长度:58225.34\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.3348秒, 路径长度:58328.28\n",
+      "执行时间:0.3232秒, 路径长度:58328.28\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:0.7189秒, 路径长度:56762.06\n",
+      "执行时间:0.7822秒, 路径长度:56762.06\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0059秒, 路径长度:59000.73\n",
+      "执行时间:0.0159秒, 路径长度:59000.73\n",
       "\n",
       "测试实例: a280.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0037秒, 路径长度:3148.11\n",
+      "执行时间:0.0087秒, 路径长度:3148.11\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0041秒, 路径长度:3148.11\n",
+      "执行时间:0.0075秒, 路径长度:3148.11\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:2.0843秒, 路径长度:3101.79\n",
+      "执行时间:2.3356秒, 路径长度:3101.79\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.3710秒, 路径长度:3182.09\n",
+      "执行时间:0.4066秒, 路径长度:3182.09\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:1.2460秒, 路径长度:2828.71\n",
+      "执行时间:1.4158秒, 路径长度:2828.71\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0127秒, 路径长度:3448.00\n",
+      "执行时间:0.0153秒, 路径长度:3448.00\n",
       "\n",
       "测试实例: pr299.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0068秒, 路径长度:59899.01\n",
+      "执行时间:0.0083秒, 路径长度:59899.01\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0074秒, 路径长度:59899.01\n",
+      "执行时间:0.0093秒, 路径长度:59899.01\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:2.4582秒, 路径长度:58124.45\n",
+      "执行时间:2.6661秒, 路径长度:58124.45\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.4082秒, 路径长度:60220.49\n",
+      "执行时间:0.3982秒, 路径长度:60220.49\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:1.5777秒, 路径长度:52408.65\n",
+      "执行时间:1.5654秒, 路径长度:52408.65\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0178秒, 路径长度:61338.05\n",
+      "执行时间:0.0157秒, 路径长度:61338.05\n",
       "\n",
       "测试实例: linhp318.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0102秒, 路径长度:54033.58\n",
+      "执行时间:0.0101秒, 路径长度:54033.58\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0113秒, 路径长度:54033.58\n",
+      "执行时间:0.0078秒, 路径长度:54033.58\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:3.5168秒, 路径长度:49454.81\n",
+      "执行时间:3.1254秒, 路径长度:49454.81\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.5548秒, 路径长度:53993.19\n",
+      "执行时间:0.4805秒, 路径长度:54033.58\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:2.2579秒, 路径长度:49153.11\n",
+      "执行时间:2.2263秒, 路径长度:49153.11\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0173秒, 路径长度:50085.92\n",
+      "执行时间:0.0260秒, 路径长度:50085.92\n",
       "\n",
       "测试实例: lin318.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0096秒, 路径长度:54033.58\n",
+      "执行时间:0.0107秒, 路径长度:54033.58\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0104秒, 路径长度:54033.58\n",
+      "执行时间:0.0097秒, 路径长度:54033.58\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:3.4641秒, 路径长度:49454.81\n",
+      "执行时间:3.2427秒, 路径长度:49454.81\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.4869秒, 路径长度:54033.58\n",
+      "执行时间:0.4752秒, 路径长度:54033.58\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:2.2018秒, 路径长度:49153.11\n",
+      "执行时间:2.0872秒, 路径长度:49153.11\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0220秒, 路径长度:50085.92\n",
+      "执行时间:0.0184秒, 路径长度:50085.92\n",
       "\n",
       "测试实例: rd400.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0169秒, 路径长度:19168.05\n",
+      "执行时间:0.0146秒, 路径长度:19168.05\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0156秒, 路径长度:19168.05\n",
+      "执行时间:0.0142秒, 路径长度:19168.05\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:6.9163秒, 路径长度:18629.98\n",
+      "执行时间:6.5915秒, 路径长度:18629.98\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.7092秒, 路径长度:19168.05\n",
+      "执行时间:0.6801秒, 路径长度:19168.05\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:4.5916秒, 路径长度:16651.71\n",
+      "执行时间:4.1070秒, 路径长度:16651.71\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0297秒, 路径长度:17599.52\n",
+      "执行时间:0.0254秒, 路径长度:17599.52\n",
       "\n",
       "测试实例: fl417.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0178秒, 路径长度:15114.12\n",
+      "执行时间:0.0150秒, 路径长度:15114.12\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0197秒, 路径长度:15114.12\n",
+      "执行时间:0.0148秒, 路径长度:15114.12\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:7.6338秒, 路径长度:14179.84\n",
+      "执行时间:6.8940秒, 路径长度:14179.84\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.7209秒, 路径长度:15256.42\n",
+      "执行时间:0.7143秒, 路径长度:15256.42\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:7.5823秒, 路径长度:13630.60\n",
+      "执行时间:7.6544秒, 路径长度:13630.60\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0236秒, 路径长度:13680.66\n",
+      "执行时间:0.0244秒, 路径长度:13680.66\n",
       "\n",
       "测试实例: gr431.tsp\n",
       "\n",
@@ -1206,119 +1206,119 @@
       "执行时间:0.0173秒, 路径长度:2516.25\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0165秒, 路径长度:2516.25\n",
+      "执行时间:0.0172秒, 路径长度:2516.25\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:8.1149秒, 路径长度:2214.43\n",
+      "执行时间:7.8334秒, 路径长度:2214.43\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.8217秒, 路径长度:2516.25\n",
+      "执行时间:0.7366秒, 路径长度:2516.25\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:5.4522秒, 路径长度:2153.00\n",
+      "执行时间:5.0698秒, 路径长度:2153.00\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0250秒, 路径长度:2263.78\n",
+      "执行时间:0.0273秒, 路径长度:2263.78\n",
       "\n",
       "测试实例: pr439.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0169秒, 路径长度:131282.09\n",
+      "执行时间:0.0160秒, 路径长度:131282.09\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0175秒, 路径长度:131282.09\n",
+      "执行时间:0.0185秒, 路径长度:131282.09\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:6.2646秒, 路径长度:130067.88\n",
+      "执行时间:8.5353秒, 路径长度:130067.88\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.4491秒, 路径长度:137778.50\n",
+      "执行时间:0.7811秒, 路径长度:137778.50\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:2.5368秒, 路径长度:118466.33\n",
+      "执行时间:4.3660秒, 路径长度:118466.33\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0130秒, 路径长度:134814.09\n",
+      "执行时间:0.0269秒, 路径长度:134814.09\n",
       "\n",
       "测试实例: pcb442.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0145秒, 路径长度:61984.05\n",
+      "执行时间:0.0234秒, 路径长度:61984.05\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0147秒, 路径长度:61984.05\n",
+      "执行时间:0.0198秒, 路径长度:61984.05\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:6.2491秒, 路径长度:60891.83\n",
+      "执行时间:8.6915秒, 路径长度:60891.83\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.5471秒, 路径长度:61234.77\n",
+      "执行时间:0.7918秒, 路径长度:61234.77\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:2.7801秒, 路径长度:54291.55\n",
+      "执行时间:4.3208秒, 路径长度:54291.55\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0156秒, 路径长度:58899.52\n",
+      "执行时间:0.0248秒, 路径长度:58899.52\n",
       "\n",
       "测试实例: d493.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0121秒, 路径长度:43646.38\n",
+      "执行时间:0.0242秒, 路径长度:43646.38\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0123秒, 路径长度:43646.38\n",
+      "执行时间:0.0226秒, 路径长度:43646.38\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:6.6914秒, 路径长度:39982.31\n",
+      "执行时间:11.6873秒, 路径长度:39982.31\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.4954秒, 路径长度:43710.70\n",
+      "执行时间:0.9321秒, 路径长度:43710.70\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:4.9482秒, 路径长度:38869.88\n",
+      "执行时间:7.6122秒, 路径长度:38869.88\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0196秒, 路径长度:43050.15\n",
+      "执行时间:0.0316秒, 路径长度:43050.15\n",
       "\n",
       "测试实例: att532.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0175秒, 路径长度:112099.45\n",
+      "执行时间:0.0280秒, 路径长度:112099.45\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0164秒, 路径长度:112099.45\n",
+      "执行时间:0.0257秒, 路径长度:112099.45\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:9.7124秒, 路径长度:102201.61\n",
+      "执行时间:14.5934秒, 路径长度:102201.61\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.6501秒, 路径长度:112099.45\n",
+      "执行时间:1.0641秒, 路径长度:112099.45\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:6.3833秒, 路径长度:99028.54\n",
+      "执行时间:9.7291秒, 路径长度:99028.54\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0229秒, 路径长度:103710.35\n",
+      "执行时间:0.0439秒, 路径长度:103710.35\n",
       "\n",
       "测试实例: ali535.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0164秒, 路径长度:2671.07\n",
+      "执行时间:0.0268秒, 路径长度:2671.07\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0157秒, 路径长度:2671.07\n",
+      "执行时间:0.0272秒, 路径长度:2671.07\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:9.8289秒, 路径长度:2366.95\n",
+      "执行时间:14.7763秒, 路径长度:2366.95\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.5881秒, 路径长度:2671.07\n",
+      "执行时间:1.0862秒, 路径长度:2671.07\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:8.2581秒, 路径长度:2269.30\n",
+      "执行时间:12.8892秒, 路径长度:2269.30\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0202秒, 路径长度:2630.32\n",
+      "执行时间:0.0354秒, 路径长度:2630.32\n",
       "\n",
       "测试实例: pa561.tsp\n",
       "\n",
@@ -1343,362 +1343,362 @@
       "测试实例: u574.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0166秒, 路径长度:46881.87\n",
+      "执行时间:0.0295秒, 路径长度:46881.87\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0237秒, 路径长度:46881.87\n",
+      "执行时间:0.0288秒, 路径长度:46881.87\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:12.5508秒, 路径长度:44144.83\n",
+      "执行时间:18.1802秒, 路径长度:44144.83\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.7088秒, 路径长度:46881.87\n",
+      "执行时间:1.2306秒, 路径长度:46881.87\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:8.8392秒, 路径长度:39154.50\n",
+      "执行时间:14.3463秒, 路径长度:39340.35\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0193秒, 路径长度:46620.28\n",
+      "执行时间:0.0401秒, 路径长度:46620.28\n",
       "\n",
       "测试实例: rat575.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0157秒, 路径长度:8449.32\n",
+      "执行时间:0.0309秒, 路径长度:8449.32\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0158秒, 路径长度:8449.32\n",
+      "执行时间:0.0292秒, 路径长度:8449.32\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:10.7083秒, 路径长度:7853.86\n",
+      "执行时间:18.5310秒, 路径长度:7853.86\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.6515秒, 路径长度:8430.71\n",
+      "执行时间:1.2574秒, 路径长度:8430.71\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:6.0627秒, 路径长度:7398.48\n",
+      "执行时间:10.7307秒, 路径长度:7398.48\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0200秒, 路径长度:7808.10\n",
+      "执行时间:0.0477秒, 路径长度:7808.10\n",
       "\n",
       "测试实例: p654.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0207秒, 路径长度:43411.56\n",
+      "执行时间:0.0402秒, 路径长度:43411.56\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0207秒, 路径长度:43411.56\n",
+      "执行时间:0.0468秒, 路径长度:43411.56\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:18.7784秒, 路径长度:40418.68\n",
+      "执行时间:28.7676秒, 路径长度:40418.68\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.9786秒, 路径长度:48824.31\n",
+      "执行时间:1.5922秒, 路径长度:48824.31\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:12.9592秒, 路径长度:38249.53\n",
+      "执行时间:21.2350秒, 路径长度:38249.53\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0310秒, 路径长度:41009.57\n",
+      "执行时间:0.0448秒, 路径长度:41009.57\n",
       "\n",
       "测试实例: d657.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0218秒, 路径长度:62176.40\n",
+      "执行时间:0.0403秒, 路径长度:62176.40\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0247秒, 路径长度:62176.40\n",
+      "执行时间:0.0383秒, 路径长度:62176.40\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:18.7046秒, 路径长度:57906.66\n",
+      "执行时间:29.4351秒, 路径长度:57906.66\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:0.9157秒, 路径长度:62176.40\n",
+      "执行时间:1.7656秒, 路径长度:62176.40\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:9.9684秒, 路径长度:54801.59\n",
+      "执行时间:17.0557秒, 路径长度:54801.59\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0275秒, 路径长度:63518.97\n",
+      "执行时间:0.0487秒, 路径长度:63518.97\n",
       "\n",
       "测试实例: gr666.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0266秒, 路径长度:4110.90\n",
+      "执行时间:0.0386秒, 路径长度:4110.90\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0237秒, 路径长度:4110.90\n",
+      "执行时间:0.0407秒, 路径长度:4110.90\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:18.7978秒, 路径长度:3670.13\n",
+      "执行时间:30.7468秒, 路径长度:3670.13\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:1.0282秒, 路径长度:4110.90\n",
+      "执行时间:1.6598秒, 路径长度:4110.90\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:19.6285秒, 路径长度:3507.73\n",
+      "执行时间:29.4371秒, 路径长度:3507.73\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0308秒, 路径长度:3920.88\n",
+      "执行时间:0.0552秒, 路径长度:3920.88\n",
       "\n",
       "测试实例: u724.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0265秒, 路径长度:55223.20\n",
+      "执行时间:0.0480秒, 路径长度:55223.20\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0262秒, 路径长度:55223.20\n",
+      "执行时间:0.0465秒, 路径长度:55223.20\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:21.4646秒, 路径长度:50245.77\n",
+      "执行时间:38.4876秒, 路径长度:50245.77\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:1.0141秒, 路径长度:52482.39\n",
+      "执行时间:1.9141秒, 路径长度:52482.39\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:13.3697秒, 路径长度:47256.49\n",
+      "执行时间:22.5706秒, 路径长度:47108.98\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0300秒, 路径长度:49538.41\n",
+      "执行时间:0.0653秒, 路径长度:49538.41\n",
       "\n",
       "测试实例: rat783.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0306秒, 路径长度:11255.07\n",
+      "执行时间:0.0604秒, 路径长度:11255.07\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0302秒, 路径长度:11255.07\n",
+      "执行时间:0.0703秒, 路径长度:11255.07\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:27.2072秒, 路径长度:10301.88\n",
+      "执行时间:52.2586秒, 路径长度:10301.88\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:1.1461秒, 路径长度:11255.07\n",
+      "执行时间:2.3729秒, 路径长度:11255.07\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:22.3859秒, 路径长度:9468.73\n",
+      "执行时间:40.4463秒, 路径长度:9468.73\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0357秒, 路径长度:11151.44\n",
+      "执行时间:0.0693秒, 路径长度:11151.44\n",
       "\n",
       "测试实例: dsj1000.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0491秒, 路径长度:24630960.10\n",
+      "执行时间:0.0898秒, 路径长度:24630960.10\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0511秒, 路径长度:24630960.10\n",
+      "执行时间:0.0894秒, 路径长度:24630960.10\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:58.0007秒, 路径长度:22291166.04\n",
+      "执行时间:106.8209秒, 路径长度:22291166.04\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:1.8257秒, 路径长度:24630960.10\n",
+      "执行时间:3.4452秒, 路径长度:24630960.10\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:59.6672秒, 路径长度:21147745.60\n",
+      "执行时间:91.5279秒, 路径长度:21147745.60\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0577秒, 路径长度:23977443.37\n",
+      "执行时间:0.0580秒, 路径长度:23977443.37\n",
       "\n",
       "测试实例: pr1002.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0483秒, 路径长度:315596.59\n",
+      "执行时间:0.0475秒, 路径长度:315596.59\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0497秒, 路径长度:315596.59\n",
+      "执行时间:0.0601秒, 路径长度:315596.59\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:66.0344秒, 路径长度:302938.90\n",
+      "执行时间:61.3033秒, 路径长度:302938.90\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:2.8392秒, 路径长度:325311.07\n",
+      "执行时间:2.4444秒, 路径长度:325311.07\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:41.2541秒, 路径长度:278851.88\n",
+      "执行时间:39.5357秒, 路径长度:278832.89\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0629秒, 路径长度:320713.45\n",
+      "执行时间:0.0474秒, 路径长度:320713.45\n",
       "\n",
       "测试实例: u1060.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0591秒, 路径长度:281635.68\n",
+      "执行时间:0.0540秒, 路径长度:281635.68\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0590秒, 路径长度:281635.68\n",
+      "执行时间:0.0525秒, 路径长度:281635.68\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:77.2518秒, 路径长度:270377.38\n",
+      "执行时间:69.3490秒, 路径长度:270377.38\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:2.6807秒, 路径长度:280689.98\n",
+      "执行时间:1.9743秒, 路径长度:280689.98\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:49.7501秒, 路径长度:241924.19\n",
+      "执行时间:46.9793秒, 路径长度:241924.19\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0943秒, 路径长度:270485.28\n",
+      "执行时间:0.1422秒, 路径长度:270485.28\n",
       "\n",
       "测试实例: vm1084.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0587秒, 路径长度:301469.23\n",
+      "执行时间:0.0574秒, 路径长度:301469.23\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0586秒, 路径长度:301469.23\n",
+      "执行时间:0.0561秒, 路径长度:301469.23\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:82.4780秒, 路径长度:277435.70\n",
+      "执行时间:74.8310秒, 路径长度:277435.70\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:2.6446秒, 路径长度:302111.10\n",
+      "执行时间:2.3008秒, 路径长度:302111.10\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:35.7943秒, 路径长度:263604.55\n",
+      "执行时间:36.6202秒, 路径长度:262266.88\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0649秒, 路径长度:273437.36\n",
+      "执行时间:0.0652秒, 路径长度:273437.36\n",
       "\n",
       "测试实例: pcb1173.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0659秒, 路径长度:70277.94\n",
+      "执行时间:0.0644秒, 路径长度:70277.94\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0646秒, 路径长度:70277.94\n",
+      "执行时间:0.0640秒, 路径长度:70277.94\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:91.5772秒, 路径长度:69010.68\n",
+      "执行时间:90.3134秒, 路径长度:69010.68\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:2.8048秒, 路径长度:70279.94\n",
+      "执行时间:2.6624秒, 路径长度:70279.94\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:45.7643秒, 路径长度:62453.05\n",
+      "执行时间:47.8099秒, 路径长度:62709.99\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0674秒, 路径长度:71441.00\n",
+      "执行时间:0.0695秒, 路径长度:71441.00\n",
       "\n",
       "测试实例: d1291.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0813秒, 路径长度:59941.24\n",
+      "执行时间:0.0822秒, 路径长度:59941.24\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0811秒, 路径长度:59941.24\n",
+      "执行时间:0.0835秒, 路径长度:59941.24\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:127.4454秒, 路径长度:59956.75\n",
+      "执行时间:126.1144秒, 路径长度:59956.75\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:2.8732秒, 路径长度:59892.04\n",
+      "执行时间:3.7137秒, 路径长度:59892.04\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:17.4007秒, 路径长度:55389.49\n",
+      "执行时间:17.3619秒, 路径长度:55389.49\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0787秒, 路径长度:62211.60\n",
+      "执行时间:0.0801秒, 路径长度:62211.60\n",
       "\n",
       "测试实例: rl1304.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0839秒, 路径长度:339797.47\n",
+      "执行时间:0.1415秒, 路径长度:339797.47\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0824秒, 路径长度:339797.47\n",
+      "执行时间:0.1519秒, 路径长度:339797.47\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:130.1252秒, 路径长度:314295.61\n",
+      "执行时间:132.5021秒, 路径长度:314295.61\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:3.2245秒, 路径长度:335160.35\n",
+      "执行时间:3.0462秒, 路径长度:335160.35\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:49.8281秒, 路径长度:284242.81\n",
+      "执行时间:54.3530秒, 路径长度:284284.10\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.1418秒, 路径长度:303550.70\n",
+      "执行时间:0.1450秒, 路径长度:303550.70\n",
       "\n",
       "测试实例: rl1323.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.0859秒, 路径长度:332094.97\n",
+      "执行时间:0.0873秒, 路径长度:332094.97\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.0859秒, 路径长度:332094.97\n",
+      "执行时间:0.0857秒, 路径长度:332094.97\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:129.8820秒, 路径长度:341512.46\n",
+      "执行时间:194.6513秒, 路径长度:341512.46\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:3.0296秒, 路径长度:331159.20\n",
+      "执行时间:3.1830秒, 路径长度:331159.20\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:44.1189秒, 路径长度:299654.18\n",
+      "执行时间:45.0123秒, 路径长度:299654.18\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0974秒, 路径长度:334237.62\n",
+      "执行时间:0.0908秒, 路径长度:334237.62\n",
       "\n",
       "测试实例: nrw1379.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.1045秒, 路径长度:70015.46\n",
+      "执行时间:0.0994秒, 路径长度:70015.46\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.1040秒, 路径长度:70015.46\n",
+      "执行时间:0.1029秒, 路径长度:70015.46\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:158.2882秒, 路径长度:66216.21\n",
+      "执行时间:161.1092秒, 路径长度:66216.21\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:3.6320秒, 路径长度:69794.61\n",
+      "执行时间:3.4999秒, 路径长度:69794.61\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:96.8080秒, 路径长度:61838.87\n",
+      "执行时间:100.5585秒, 路径长度:61838.87\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.1103秒, 路径长度:68362.91\n",
+      "执行时间:0.1221秒, 路径长度:68362.91\n",
       "\n",
       "测试实例: fl1400.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.1030秒, 路径长度:26971.88\n",
+      "执行时间:0.1201秒, 路径长度:26971.88\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.1028秒, 路径长度:26971.88\n",
+      "执行时间:0.1193秒, 路径长度:26971.88\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:186.6609秒, 路径长度:22955.32\n",
+      "执行时间:163.7658秒, 路径长度:22955.32\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:3.4932秒, 路径长度:27057.04\n",
+      "执行时间:3.8870秒, 路径长度:27057.04\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:265.7287秒, 路径长度:22420.49\n",
+      "执行时间:205.7018秒, 路径长度:22420.49\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.1604秒, 路径长度:23757.04\n",
+      "执行时间:0.0907秒, 路径长度:23757.04\n",
       "\n",
       "测试实例: u1432.tsp\n",
       "\n",
       "使用算法: 贪心算法\n",
-      "执行时间:0.2142秒, 路径长度:188815.01\n",
+      "执行时间:0.1072秒, 路径长度:188815.01\n",
       "\n",
       "使用算法: 最近邻算法\n",
-      "执行时间:0.1910秒, 路径长度:188815.01\n",
+      "执行时间:0.1022秒, 路径长度:188815.01\n",
       "\n",
       "使用算法: 插入法\n",
-      "执行时间:212.7076秒, 路径长度:171110.62\n",
+      "执行时间:162.7644秒, 路径长度:171110.62\n",
       "\n",
       "使用算法: EoH-TSP\n",
-      "执行时间:3.5985秒, 路径长度:196453.25\n",
+      "执行时间:3.8517秒, 路径长度:196453.25\n",
       "\n",
       "使用算法: AAD-TSP\n",
-      "执行时间:79.1341秒, 路径长度:167338.88\n",
+      "执行时间:85.9519秒, 路径长度:167338.88\n",
       "\n",
       "使用算法: MEoH-TSP\n",
-      "执行时间:0.0944秒, 路径长度:173489.17\n",
+      "执行时间:0.1026秒, 路径长度:173489.17\n",
       "\n",
       "所有算法在各个实例上的表现:\n",
       "\n",
@@ -1777,80 +1777,80 @@
       "  nrw1379.tsp: 路径长度 = 70015.46\n",
       "  fl1400.tsp: 路径长度 = 26971.88\n",
       "  u1432.tsp: 路径长度 = 188815.01\n",
-      "  burma14.tsp: 执行时间 = 0.0001秒\n",
+      "  burma14.tsp: 执行时间 = 0.0000秒\n",
       "  ulysses16.tsp: 执行时间 = 0.0000秒\n",
-      "  ulysses22.tsp: 执行时间 = 0.0001秒\n",
+      "  ulysses22.tsp: 执行时间 = 0.0000秒\n",
       "  dantzig42.tsp: 执行时间 = 0.0000秒\n",
       "  att48.tsp: 执行时间 = 0.0003秒\n",
-      "  eil51.tsp: 执行时间 = 0.0004秒\n",
-      "  berlin52.tsp: 执行时间 = 0.0003秒\n",
+      "  eil51.tsp: 执行时间 = 0.0005秒\n",
+      "  berlin52.tsp: 执行时间 = 0.0004秒\n",
       "  st70.tsp: 执行时间 = 0.0006秒\n",
-      "  pr76.tsp: 执行时间 = 0.0003秒\n",
-      "  eil76.tsp: 执行时间 = 0.0008秒\n",
-      "  gr96.tsp: 执行时间 = 0.0010秒\n",
-      "  rat99.tsp: 执行时间 = 0.0011秒\n",
-      "  rd100.tsp: 执行时间 = 0.0015秒\n",
-      "  kroB100.tsp: 执行时间 = 0.0009秒\n",
+      "  pr76.tsp: 执行时间 = 0.0008秒\n",
+      "  eil76.tsp: 执行时间 = 0.0009秒\n",
+      "  gr96.tsp: 执行时间 = 0.0009秒\n",
+      "  rat99.tsp: 执行时间 = 0.0013秒\n",
+      "  rd100.tsp: 执行时间 = 0.0005秒\n",
+      "  kroB100.tsp: 执行时间 = 0.0015秒\n",
       "  kroD100.tsp: 执行时间 = 0.0012秒\n",
       "  kroA100.tsp: 执行时间 = 0.0015秒\n",
-      "  kroC100.tsp: 执行时间 = 0.0010秒\n",
+      "  kroC100.tsp: 执行时间 = 0.0012秒\n",
       "  kroE100.tsp: 执行时间 = 0.0011秒\n",
       "  eil101.tsp: 执行时间 = 0.0011秒\n",
-      "  lin105.tsp: 执行时间 = 0.0011秒\n",
-      "  pr107.tsp: 执行时间 = 0.0018秒\n",
-      "  pr124.tsp: 执行时间 = 0.0015秒\n",
-      "  bier127.tsp: 执行时间 = 0.0018秒\n",
+      "  lin105.tsp: 执行时间 = 0.0014秒\n",
+      "  pr107.tsp: 执行时间 = 0.0016秒\n",
+      "  pr124.tsp: 执行时间 = 0.0017秒\n",
+      "  bier127.tsp: 执行时间 = 0.0015秒\n",
       "  ch130.tsp: 执行时间 = 0.0017秒\n",
-      "  pr136.tsp: 执行时间 = 0.0023秒\n",
-      "  gr137.tsp: 执行时间 = 0.0021秒\n",
-      "  pr144.tsp: 执行时间 = 0.0020秒\n",
-      "  kroA150.tsp: 执行时间 = 0.0019秒\n",
-      "  ch150.tsp: 执行时间 = 0.0020秒\n",
-      "  kroB150.tsp: 执行时间 = 0.0022秒\n",
-      "  pr152.tsp: 执行时间 = 0.0021秒\n",
-      "  u159.tsp: 执行时间 = 0.0023秒\n",
-      "  rat195.tsp: 执行时间 = 0.0039秒\n",
-      "  d198.tsp: 执行时间 = 0.0044秒\n",
-      "  kroB200.tsp: 执行时间 = 0.0036秒\n",
-      "  kroA200.tsp: 执行时间 = 0.0043秒\n",
-      "  gr202.tsp: 执行时间 = 0.0043秒\n",
-      "  tsp225.tsp: 执行时间 = 0.0051秒\n",
-      "  ts225.tsp: 执行时间 = 0.0057秒\n",
-      "  pr226.tsp: 执行时间 = 0.0040秒\n",
-      "  gr229.tsp: 执行时间 = 0.0048秒\n",
+      "  pr136.tsp: 执行时间 = 0.0020秒\n",
+      "  gr137.tsp: 执行时间 = 0.0024秒\n",
+      "  pr144.tsp: 执行时间 = 0.0025秒\n",
+      "  kroA150.tsp: 执行时间 = 0.0025秒\n",
+      "  ch150.tsp: 执行时间 = 0.0028秒\n",
+      "  kroB150.tsp: 执行时间 = 0.0020秒\n",
+      "  pr152.tsp: 执行时间 = 0.0025秒\n",
+      "  u159.tsp: 执行时间 = 0.0022秒\n",
+      "  rat195.tsp: 执行时间 = 0.0036秒\n",
+      "  d198.tsp: 执行时间 = 0.0048秒\n",
+      "  kroB200.tsp: 执行时间 = 0.0039秒\n",
+      "  kroA200.tsp: 执行时间 = 0.0038秒\n",
+      "  gr202.tsp: 执行时间 = 0.0033秒\n",
+      "  tsp225.tsp: 执行时间 = 0.0040秒\n",
+      "  ts225.tsp: 执行时间 = 0.0055秒\n",
+      "  pr226.tsp: 执行时间 = 0.0047秒\n",
+      "  gr229.tsp: 执行时间 = 0.0060秒\n",
       "  gil262.tsp: 执行时间 = 0.0067秒\n",
-      "  pr264.tsp: 执行时间 = 0.0071秒\n",
-      "  a280.tsp: 执行时间 = 0.0037秒\n",
-      "  pr299.tsp: 执行时间 = 0.0068秒\n",
-      "  linhp318.tsp: 执行时间 = 0.0102秒\n",
-      "  lin318.tsp: 执行时间 = 0.0096秒\n",
-      "  rd400.tsp: 执行时间 = 0.0169秒\n",
-      "  fl417.tsp: 执行时间 = 0.0178秒\n",
+      "  pr264.tsp: 执行时间 = 0.0072秒\n",
+      "  a280.tsp: 执行时间 = 0.0087秒\n",
+      "  pr299.tsp: 执行时间 = 0.0083秒\n",
+      "  linhp318.tsp: 执行时间 = 0.0101秒\n",
+      "  lin318.tsp: 执行时间 = 0.0107秒\n",
+      "  rd400.tsp: 执行时间 = 0.0146秒\n",
+      "  fl417.tsp: 执行时间 = 0.0150秒\n",
       "  gr431.tsp: 执行时间 = 0.0173秒\n",
-      "  pr439.tsp: 执行时间 = 0.0169秒\n",
-      "  pcb442.tsp: 执行时间 = 0.0145秒\n",
-      "  d493.tsp: 执行时间 = 0.0121秒\n",
-      "  att532.tsp: 执行时间 = 0.0175秒\n",
-      "  ali535.tsp: 执行时间 = 0.0164秒\n",
+      "  pr439.tsp: 执行时间 = 0.0160秒\n",
+      "  pcb442.tsp: 执行时间 = 0.0234秒\n",
+      "  d493.tsp: 执行时间 = 0.0242秒\n",
+      "  att532.tsp: 执行时间 = 0.0280秒\n",
+      "  ali535.tsp: 执行时间 = 0.0268秒\n",
       "  pa561.tsp: 执行时间 = 0.0000秒\n",
-      "  u574.tsp: 执行时间 = 0.0166秒\n",
-      "  rat575.tsp: 执行时间 = 0.0157秒\n",
-      "  p654.tsp: 执行时间 = 0.0207秒\n",
-      "  d657.tsp: 执行时间 = 0.0218秒\n",
-      "  gr666.tsp: 执行时间 = 0.0266秒\n",
-      "  u724.tsp: 执行时间 = 0.0265秒\n",
-      "  rat783.tsp: 执行时间 = 0.0306秒\n",
-      "  dsj1000.tsp: 执行时间 = 0.0491秒\n",
-      "  pr1002.tsp: 执行时间 = 0.0483秒\n",
-      "  u1060.tsp: 执行时间 = 0.0591秒\n",
-      "  vm1084.tsp: 执行时间 = 0.0587秒\n",
-      "  pcb1173.tsp: 执行时间 = 0.0659秒\n",
-      "  d1291.tsp: 执行时间 = 0.0813秒\n",
-      "  rl1304.tsp: 执行时间 = 0.0839秒\n",
-      "  rl1323.tsp: 执行时间 = 0.0859秒\n",
-      "  nrw1379.tsp: 执行时间 = 0.1045秒\n",
-      "  fl1400.tsp: 执行时间 = 0.1030秒\n",
-      "  u1432.tsp: 执行时间 = 0.2142秒\n",
+      "  u574.tsp: 执行时间 = 0.0295秒\n",
+      "  rat575.tsp: 执行时间 = 0.0309秒\n",
+      "  p654.tsp: 执行时间 = 0.0402秒\n",
+      "  d657.tsp: 执行时间 = 0.0403秒\n",
+      "  gr666.tsp: 执行时间 = 0.0386秒\n",
+      "  u724.tsp: 执行时间 = 0.0480秒\n",
+      "  rat783.tsp: 执行时间 = 0.0604秒\n",
+      "  dsj1000.tsp: 执行时间 = 0.0898秒\n",
+      "  pr1002.tsp: 执行时间 = 0.0475秒\n",
+      "  u1060.tsp: 执行时间 = 0.0540秒\n",
+      "  vm1084.tsp: 执行时间 = 0.0574秒\n",
+      "  pcb1173.tsp: 执行时间 = 0.0644秒\n",
+      "  d1291.tsp: 执行时间 = 0.0822秒\n",
+      "  rl1304.tsp: 执行时间 = 0.1415秒\n",
+      "  rl1323.tsp: 执行时间 = 0.0873秒\n",
+      "  nrw1379.tsp: 执行时间 = 0.0994秒\n",
+      "  fl1400.tsp: 执行时间 = 0.1201秒\n",
+      "  u1432.tsp: 执行时间 = 0.1072秒\n",
       "\n",
       "最近邻算法:\n",
       "  burma14.tsp: 路径长度 = 38.69\n",
@@ -1931,76 +1931,76 @@
       "  ulysses16.tsp: 执行时间 = 0.0000秒\n",
       "  ulysses22.tsp: 执行时间 = 0.0001秒\n",
       "  dantzig42.tsp: 执行时间 = 0.0000秒\n",
-      "  att48.tsp: 执行时间 = 0.0003秒\n",
+      "  att48.tsp: 执行时间 = 0.0002秒\n",
       "  eil51.tsp: 执行时间 = 0.0004秒\n",
-      "  berlin52.tsp: 执行时间 = 0.0005秒\n",
-      "  st70.tsp: 执行时间 = 0.0005秒\n",
-      "  pr76.tsp: 执行时间 = 0.0003秒\n",
-      "  eil76.tsp: 执行时间 = 0.0006秒\n",
-      "  gr96.tsp: 执行时间 = 0.0009秒\n",
-      "  rat99.tsp: 执行时间 = 0.0007秒\n",
+      "  berlin52.tsp: 执行时间 = 0.0002秒\n",
+      "  st70.tsp: 执行时间 = 0.0006秒\n",
+      "  pr76.tsp: 执行时间 = 0.0007秒\n",
+      "  eil76.tsp: 执行时间 = 0.0007秒\n",
+      "  gr96.tsp: 执行时间 = 0.0011秒\n",
+      "  rat99.tsp: 执行时间 = 0.0011秒\n",
       "  rd100.tsp: 执行时间 = 0.0012秒\n",
-      "  kroB100.tsp: 执行时间 = 0.0012秒\n",
-      "  kroD100.tsp: 执行时间 = 0.0010秒\n",
+      "  kroB100.tsp: 执行时间 = 0.0013秒\n",
+      "  kroD100.tsp: 执行时间 = 0.0007秒\n",
       "  kroA100.tsp: 执行时间 = 0.0010秒\n",
-      "  kroC100.tsp: 执行时间 = 0.0012秒\n",
-      "  kroE100.tsp: 执行时间 = 0.0013秒\n",
-      "  eil101.tsp: 执行时间 = 0.0015秒\n",
+      "  kroC100.tsp: 执行时间 = 0.0015秒\n",
+      "  kroE100.tsp: 执行时间 = 0.0008秒\n",
+      "  eil101.tsp: 执行时间 = 0.0013秒\n",
       "  lin105.tsp: 执行时间 = 0.0012秒\n",
-      "  pr107.tsp: 执行时间 = 0.0015秒\n",
-      "  pr124.tsp: 执行时间 = 0.0010秒\n",
-      "  bier127.tsp: 执行时间 = 0.0018秒\n",
-      "  ch130.tsp: 执行时间 = 0.0017秒\n",
-      "  pr136.tsp: 执行时间 = 0.0019秒\n",
-      "  gr137.tsp: 执行时间 = 0.0022秒\n",
+      "  pr107.tsp: 执行时间 = 0.0014秒\n",
+      "  pr124.tsp: 执行时间 = 0.0015秒\n",
+      "  bier127.tsp: 执行时间 = 0.0016秒\n",
+      "  ch130.tsp: 执行时间 = 0.0020秒\n",
+      "  pr136.tsp: 执行时间 = 0.0014秒\n",
+      "  gr137.tsp: 执行时间 = 0.0017秒\n",
       "  pr144.tsp: 执行时间 = 0.0021秒\n",
-      "  kroA150.tsp: 执行时间 = 0.0022秒\n",
+      "  kroA150.tsp: 执行时间 = 0.0019秒\n",
       "  ch150.tsp: 执行时间 = 0.0020秒\n",
-      "  kroB150.tsp: 执行时间 = 0.0026秒\n",
-      "  pr152.tsp: 执行时间 = 0.0023秒\n",
-      "  u159.tsp: 执行时间 = 0.0026秒\n",
-      "  rat195.tsp: 执行时间 = 0.0046秒\n",
-      "  d198.tsp: 执行时间 = 0.0048秒\n",
-      "  kroB200.tsp: 执行时间 = 0.0037秒\n",
-      "  kroA200.tsp: 执行时间 = 0.0037秒\n",
-      "  gr202.tsp: 执行时间 = 0.0044秒\n",
-      "  tsp225.tsp: 执行时间 = 0.0053秒\n",
-      "  ts225.tsp: 执行时间 = 0.0037秒\n",
-      "  pr226.tsp: 执行时间 = 0.0040秒\n",
-      "  gr229.tsp: 执行时间 = 0.0047秒\n",
-      "  gil262.tsp: 执行时间 = 0.0060秒\n",
-      "  pr264.tsp: 执行时间 = 0.0069秒\n",
-      "  a280.tsp: 执行时间 = 0.0041秒\n",
-      "  pr299.tsp: 执行时间 = 0.0074秒\n",
-      "  linhp318.tsp: 执行时间 = 0.0113秒\n",
-      "  lin318.tsp: 执行时间 = 0.0104秒\n",
-      "  rd400.tsp: 执行时间 = 0.0156秒\n",
-      "  fl417.tsp: 执行时间 = 0.0197秒\n",
-      "  gr431.tsp: 执行时间 = 0.0165秒\n",
-      "  pr439.tsp: 执行时间 = 0.0175秒\n",
-      "  pcb442.tsp: 执行时间 = 0.0147秒\n",
-      "  d493.tsp: 执行时间 = 0.0123秒\n",
-      "  att532.tsp: 执行时间 = 0.0164秒\n",
-      "  ali535.tsp: 执行时间 = 0.0157秒\n",
+      "  kroB150.tsp: 执行时间 = 0.0024秒\n",
+      "  pr152.tsp: 执行时间 = 0.0022秒\n",
+      "  u159.tsp: 执行时间 = 0.0023秒\n",
+      "  rat195.tsp: 执行时间 = 0.0037秒\n",
+      "  d198.tsp: 执行时间 = 0.0040秒\n",
+      "  kroB200.tsp: 执行时间 = 0.0034秒\n",
+      "  kroA200.tsp: 执行时间 = 0.0039秒\n",
+      "  gr202.tsp: 执行时间 = 0.0033秒\n",
+      "  tsp225.tsp: 执行时间 = 0.0047秒\n",
+      "  ts225.tsp: 执行时间 = 0.0044秒\n",
+      "  pr226.tsp: 执行时间 = 0.0038秒\n",
+      "  gr229.tsp: 执行时间 = 0.0057秒\n",
+      "  gil262.tsp: 执行时间 = 0.0070秒\n",
+      "  pr264.tsp: 执行时间 = 0.0068秒\n",
+      "  a280.tsp: 执行时间 = 0.0075秒\n",
+      "  pr299.tsp: 执行时间 = 0.0093秒\n",
+      "  linhp318.tsp: 执行时间 = 0.0078秒\n",
+      "  lin318.tsp: 执行时间 = 0.0097秒\n",
+      "  rd400.tsp: 执行时间 = 0.0142秒\n",
+      "  fl417.tsp: 执行时间 = 0.0148秒\n",
+      "  gr431.tsp: 执行时间 = 0.0172秒\n",
+      "  pr439.tsp: 执行时间 = 0.0185秒\n",
+      "  pcb442.tsp: 执行时间 = 0.0198秒\n",
+      "  d493.tsp: 执行时间 = 0.0226秒\n",
+      "  att532.tsp: 执行时间 = 0.0257秒\n",
+      "  ali535.tsp: 执行时间 = 0.0272秒\n",
       "  pa561.tsp: 执行时间 = 0.0000秒\n",
-      "  u574.tsp: 执行时间 = 0.0237秒\n",
-      "  rat575.tsp: 执行时间 = 0.0158秒\n",
-      "  p654.tsp: 执行时间 = 0.0207秒\n",
-      "  d657.tsp: 执行时间 = 0.0247秒\n",
-      "  gr666.tsp: 执行时间 = 0.0237秒\n",
-      "  u724.tsp: 执行时间 = 0.0262秒\n",
-      "  rat783.tsp: 执行时间 = 0.0302秒\n",
-      "  dsj1000.tsp: 执行时间 = 0.0511秒\n",
-      "  pr1002.tsp: 执行时间 = 0.0497秒\n",
-      "  u1060.tsp: 执行时间 = 0.0590秒\n",
-      "  vm1084.tsp: 执行时间 = 0.0586秒\n",
-      "  pcb1173.tsp: 执行时间 = 0.0646秒\n",
-      "  d1291.tsp: 执行时间 = 0.0811秒\n",
-      "  rl1304.tsp: 执行时间 = 0.0824秒\n",
-      "  rl1323.tsp: 执行时间 = 0.0859秒\n",
-      "  nrw1379.tsp: 执行时间 = 0.1040秒\n",
-      "  fl1400.tsp: 执行时间 = 0.1028秒\n",
-      "  u1432.tsp: 执行时间 = 0.1910秒\n",
+      "  u574.tsp: 执行时间 = 0.0288秒\n",
+      "  rat575.tsp: 执行时间 = 0.0292秒\n",
+      "  p654.tsp: 执行时间 = 0.0468秒\n",
+      "  d657.tsp: 执行时间 = 0.0383秒\n",
+      "  gr666.tsp: 执行时间 = 0.0407秒\n",
+      "  u724.tsp: 执行时间 = 0.0465秒\n",
+      "  rat783.tsp: 执行时间 = 0.0703秒\n",
+      "  dsj1000.tsp: 执行时间 = 0.0894秒\n",
+      "  pr1002.tsp: 执行时间 = 0.0601秒\n",
+      "  u1060.tsp: 执行时间 = 0.0525秒\n",
+      "  vm1084.tsp: 执行时间 = 0.0561秒\n",
+      "  pcb1173.tsp: 执行时间 = 0.0640秒\n",
+      "  d1291.tsp: 执行时间 = 0.0835秒\n",
+      "  rl1304.tsp: 执行时间 = 0.1519秒\n",
+      "  rl1323.tsp: 执行时间 = 0.0857秒\n",
+      "  nrw1379.tsp: 执行时间 = 0.1029秒\n",
+      "  fl1400.tsp: 执行时间 = 0.1193秒\n",
+      "  u1432.tsp: 执行时间 = 0.1022秒\n",
       "\n",
       "插入法:\n",
       "  burma14.tsp: 路径长度 = 32.44\n",
@@ -2077,91 +2077,91 @@
       "  nrw1379.tsp: 路径长度 = 66216.21\n",
       "  fl1400.tsp: 路径长度 = 22955.32\n",
       "  u1432.tsp: 路径长度 = 171110.62\n",
-      "  burma14.tsp: 执行时间 = 0.0010秒\n",
-      "  ulysses16.tsp: 执行时间 = 0.0004秒\n",
-      "  ulysses22.tsp: 执行时间 = 0.0011秒\n",
+      "  burma14.tsp: 执行时间 = 0.0004秒\n",
+      "  ulysses16.tsp: 执行时间 = 0.0007秒\n",
+      "  ulysses22.tsp: 执行时间 = 0.0010秒\n",
       "  dantzig42.tsp: 执行时间 = inf秒\n",
-      "  att48.tsp: 执行时间 = 0.0112秒\n",
-      "  eil51.tsp: 执行时间 = 0.0150秒\n",
+      "  att48.tsp: 执行时间 = 0.0124秒\n",
+      "  eil51.tsp: 执行时间 = 0.0146秒\n",
       "  berlin52.tsp: 执行时间 = 0.0169秒\n",
-      "  st70.tsp: 执行时间 = 0.0393秒\n",
-      "  pr76.tsp: 执行时间 = 0.0463秒\n",
-      "  eil76.tsp: 执行时间 = 0.0473秒\n",
-      "  gr96.tsp: 执行时间 = 0.0832秒\n",
-      "  rat99.tsp: 执行时间 = 0.0929秒\n",
-      "  rd100.tsp: 执行时间 = 0.0966秒\n",
-      "  kroB100.tsp: 执行时间 = 0.0981秒\n",
-      "  kroD100.tsp: 执行时间 = 0.0972秒\n",
-      "  kroA100.tsp: 执行时间 = 0.1088秒\n",
-      "  kroC100.tsp: 执行时间 = 0.1006秒\n",
-      "  kroE100.tsp: 执行时间 = 0.1067秒\n",
-      "  eil101.tsp: 执行时间 = 0.1047秒\n",
-      "  lin105.tsp: 执行时间 = 0.1178秒\n",
-      "  pr107.tsp: 执行时间 = 0.1222秒\n",
-      "  pr124.tsp: 执行时间 = 0.1867秒\n",
-      "  bier127.tsp: 执行时间 = 0.2051秒\n",
-      "  ch130.tsp: 执行时间 = 0.2264秒\n",
-      "  pr136.tsp: 执行时间 = 0.2532秒\n",
-      "  gr137.tsp: 执行时间 = 0.2709秒\n",
-      "  pr144.tsp: 执行时间 = 0.2869秒\n",
-      "  kroA150.tsp: 执行时间 = 0.3287秒\n",
-      "  ch150.tsp: 执行时间 = 0.3128秒\n",
-      "  kroB150.tsp: 执行时间 = 0.3337秒\n",
-      "  pr152.tsp: 执行时间 = 0.3738秒\n",
-      "  u159.tsp: 执行时间 = 0.4197秒\n",
-      "  rat195.tsp: 执行时间 = 0.7990秒\n",
-      "  d198.tsp: 执行时间 = 0.7791秒\n",
-      "  kroB200.tsp: 执行时间 = 0.8396秒\n",
-      "  kroA200.tsp: 执行时间 = 0.8220秒\n",
-      "  gr202.tsp: 执行时间 = 0.8180秒\n",
-      "  tsp225.tsp: 执行时间 = 1.1301秒\n",
-      "  ts225.tsp: 执行时间 = 1.0775秒\n",
-      "  pr226.tsp: 执行时间 = 1.1298秒\n",
-      "  gr229.tsp: 执行时间 = 1.1679秒\n",
-      "  gil262.tsp: 执行时间 = 1.7432秒\n",
-      "  pr264.tsp: 执行时间 = 1.8694秒\n",
-      "  a280.tsp: 执行时间 = 2.0843秒\n",
-      "  pr299.tsp: 执行时间 = 2.4582秒\n",
-      "  linhp318.tsp: 执行时间 = 3.5168秒\n",
-      "  lin318.tsp: 执行时间 = 3.4641秒\n",
-      "  rd400.tsp: 执行时间 = 6.9163秒\n",
-      "  fl417.tsp: 执行时间 = 7.6338秒\n",
-      "  gr431.tsp: 执行时间 = 8.1149秒\n",
-      "  pr439.tsp: 执行时间 = 6.2646秒\n",
-      "  pcb442.tsp: 执行时间 = 6.2491秒\n",
-      "  d493.tsp: 执行时间 = 6.6914秒\n",
-      "  att532.tsp: 执行时间 = 9.7124秒\n",
-      "  ali535.tsp: 执行时间 = 9.8289秒\n",
+      "  st70.tsp: 执行时间 = 0.0399秒\n",
+      "  pr76.tsp: 执行时间 = 0.0511秒\n",
+      "  eil76.tsp: 执行时间 = 0.0430秒\n",
+      "  gr96.tsp: 执行时间 = 0.0923秒\n",
+      "  rat99.tsp: 执行时间 = 0.1136秒\n",
+      "  rd100.tsp: 执行时间 = 0.1072秒\n",
+      "  kroB100.tsp: 执行时间 = 0.1206秒\n",
+      "  kroD100.tsp: 执行时间 = 0.1119秒\n",
+      "  kroA100.tsp: 执行时间 = 0.0981秒\n",
+      "  kroC100.tsp: 执行时间 = 0.0983秒\n",
+      "  kroE100.tsp: 执行时间 = 0.1026秒\n",
+      "  eil101.tsp: 执行时间 = 0.1086秒\n",
+      "  lin105.tsp: 执行时间 = 0.1155秒\n",
+      "  pr107.tsp: 执行时间 = 0.1403秒\n",
+      "  pr124.tsp: 执行时间 = 0.2034秒\n",
+      "  bier127.tsp: 执行时间 = 0.2007秒\n",
+      "  ch130.tsp: 执行时间 = 0.2338秒\n",
+      "  pr136.tsp: 执行时间 = 0.2884秒\n",
+      "  gr137.tsp: 执行时间 = 0.2412秒\n",
+      "  pr144.tsp: 执行时间 = 0.3768秒\n",
+      "  kroA150.tsp: 执行时间 = 0.3564秒\n",
+      "  ch150.tsp: 执行时间 = 0.3516秒\n",
+      "  kroB150.tsp: 执行时间 = 0.3577秒\n",
+      "  pr152.tsp: 执行时间 = 0.3534秒\n",
+      "  u159.tsp: 执行时间 = 0.3635秒\n",
+      "  rat195.tsp: 执行时间 = 0.8294秒\n",
+      "  d198.tsp: 执行时间 = 0.8395秒\n",
+      "  kroB200.tsp: 执行时间 = 0.8084秒\n",
+      "  kroA200.tsp: 执行时间 = 0.8769秒\n",
+      "  gr202.tsp: 执行时间 = 0.8244秒\n",
+      "  tsp225.tsp: 执行时间 = 1.2282秒\n",
+      "  ts225.tsp: 执行时间 = 1.1208秒\n",
+      "  pr226.tsp: 执行时间 = 1.1522秒\n",
+      "  gr229.tsp: 执行时间 = 1.2088秒\n",
+      "  gil262.tsp: 执行时间 = 1.8069秒\n",
+      "  pr264.tsp: 执行时间 = 1.9408秒\n",
+      "  a280.tsp: 执行时间 = 2.3356秒\n",
+      "  pr299.tsp: 执行时间 = 2.6661秒\n",
+      "  linhp318.tsp: 执行时间 = 3.1254秒\n",
+      "  lin318.tsp: 执行时间 = 3.2427秒\n",
+      "  rd400.tsp: 执行时间 = 6.5915秒\n",
+      "  fl417.tsp: 执行时间 = 6.8940秒\n",
+      "  gr431.tsp: 执行时间 = 7.8334秒\n",
+      "  pr439.tsp: 执行时间 = 8.5353秒\n",
+      "  pcb442.tsp: 执行时间 = 8.6915秒\n",
+      "  d493.tsp: 执行时间 = 11.6873秒\n",
+      "  att532.tsp: 执行时间 = 14.5934秒\n",
+      "  ali535.tsp: 执行时间 = 14.7763秒\n",
       "  pa561.tsp: 执行时间 = inf秒\n",
-      "  u574.tsp: 执行时间 = 12.5508秒\n",
-      "  rat575.tsp: 执行时间 = 10.7083秒\n",
-      "  p654.tsp: 执行时间 = 18.7784秒\n",
-      "  d657.tsp: 执行时间 = 18.7046秒\n",
-      "  gr666.tsp: 执行时间 = 18.7978秒\n",
-      "  u724.tsp: 执行时间 = 21.4646秒\n",
-      "  rat783.tsp: 执行时间 = 27.2072秒\n",
-      "  dsj1000.tsp: 执行时间 = 58.0007秒\n",
-      "  pr1002.tsp: 执行时间 = 66.0344秒\n",
-      "  u1060.tsp: 执行时间 = 77.2518秒\n",
-      "  vm1084.tsp: 执行时间 = 82.4780秒\n",
-      "  pcb1173.tsp: 执行时间 = 91.5772秒\n",
-      "  d1291.tsp: 执行时间 = 127.4454秒\n",
-      "  rl1304.tsp: 执行时间 = 130.1252秒\n",
-      "  rl1323.tsp: 执行时间 = 129.8820秒\n",
-      "  nrw1379.tsp: 执行时间 = 158.2882秒\n",
-      "  fl1400.tsp: 执行时间 = 186.6609秒\n",
-      "  u1432.tsp: 执行时间 = 212.7076秒\n",
+      "  u574.tsp: 执行时间 = 18.1802秒\n",
+      "  rat575.tsp: 执行时间 = 18.5310秒\n",
+      "  p654.tsp: 执行时间 = 28.7676秒\n",
+      "  d657.tsp: 执行时间 = 29.4351秒\n",
+      "  gr666.tsp: 执行时间 = 30.7468秒\n",
+      "  u724.tsp: 执行时间 = 38.4876秒\n",
+      "  rat783.tsp: 执行时间 = 52.2586秒\n",
+      "  dsj1000.tsp: 执行时间 = 106.8209秒\n",
+      "  pr1002.tsp: 执行时间 = 61.3033秒\n",
+      "  u1060.tsp: 执行时间 = 69.3490秒\n",
+      "  vm1084.tsp: 执行时间 = 74.8310秒\n",
+      "  pcb1173.tsp: 执行时间 = 90.3134秒\n",
+      "  d1291.tsp: 执行时间 = 126.1144秒\n",
+      "  rl1304.tsp: 执行时间 = 132.5021秒\n",
+      "  rl1323.tsp: 执行时间 = 194.6513秒\n",
+      "  nrw1379.tsp: 执行时间 = 161.1092秒\n",
+      "  fl1400.tsp: 执行时间 = 163.7658秒\n",
+      "  u1432.tsp: 执行时间 = 162.7644秒\n",
       "\n",
       "EoH-TSP:\n",
       "  burma14.tsp: 路径长度 = 38.69\n",
-      "  ulysses16.tsp: 路径长度 = 88.25\n",
-      "  ulysses22.tsp: 路径长度 = 82.21\n",
+      "  ulysses16.tsp: 路径长度 = 76.87\n",
+      "  ulysses22.tsp: 路径长度 = 89.64\n",
       "  dantzig42.tsp: 路径长度 = inf\n",
       "  att48.tsp: 路径长度 = 40526.42\n",
       "  eil51.tsp: 路径长度 = 513.61\n",
       "  berlin52.tsp: 路径长度 = 8980.92\n",
-      "  st70.tsp: 路径长度 = 800.35\n",
-      "  pr76.tsp: 路径长度 = 141744.29\n",
+      "  st70.tsp: 路径长度 = 805.53\n",
+      "  pr76.tsp: 路径长度 = 140565.41\n",
       "  eil76.tsp: 路径长度 = 669.24\n",
       "  gr96.tsp: 路径长度 = 707.09\n",
       "  rat99.tsp: 路径长度 = 1564.72\n",
@@ -2186,7 +2186,7 @@
       "  pr152.tsp: 路径长度 = 85702.95\n",
       "  u159.tsp: 路径长度 = 57436.69\n",
       "  rat195.tsp: 路径长度 = 2761.96\n",
-      "  d198.tsp: 路径长度 = 18620.07\n",
+      "  d198.tsp: 路径长度 = 18605.19\n",
       "  kroB200.tsp: 路径长度 = 36981.59\n",
       "  kroA200.tsp: 路径长度 = 35798.41\n",
       "  gr202.tsp: 路径长度 = 619.40\n",
@@ -2198,7 +2198,7 @@
       "  pr264.tsp: 路径长度 = 58328.28\n",
       "  a280.tsp: 路径长度 = 3182.09\n",
       "  pr299.tsp: 路径长度 = 60220.49\n",
-      "  linhp318.tsp: 路径长度 = 53993.19\n",
+      "  linhp318.tsp: 路径长度 = 54033.58\n",
       "  lin318.tsp: 路径长度 = 54033.58\n",
       "  rd400.tsp: 路径长度 = 19168.05\n",
       "  fl417.tsp: 路径长度 = 15256.42\n",
@@ -2227,118 +2227,118 @@
       "  nrw1379.tsp: 路径长度 = 69794.61\n",
       "  fl1400.tsp: 路径长度 = 27057.04\n",
       "  u1432.tsp: 路径长度 = 196453.25\n",
-      "  burma14.tsp: 执行时间 = 0.0136秒\n",
-      "  ulysses16.tsp: 执行时间 = 0.0113秒\n",
-      "  ulysses22.tsp: 执行时间 = 0.0144秒\n",
+      "  burma14.tsp: 执行时间 = 0.0120秒\n",
+      "  ulysses16.tsp: 执行时间 = 0.0099秒\n",
+      "  ulysses22.tsp: 执行时间 = 0.0160秒\n",
       "  dantzig42.tsp: 执行时间 = inf秒\n",
-      "  att48.tsp: 执行时间 = 0.0363秒\n",
-      "  eil51.tsp: 执行时间 = 0.0373秒\n",
-      "  berlin52.tsp: 执行时间 = 0.0456秒\n",
-      "  st70.tsp: 执行时间 = 0.0635秒\n",
-      "  pr76.tsp: 执行时间 = 0.0707秒\n",
-      "  eil76.tsp: 执行时间 = 0.0599秒\n",
-      "  gr96.tsp: 执行时间 = 0.0823秒\n",
-      "  rat99.tsp: 执行时间 = 0.0926秒\n",
-      "  rd100.tsp: 执行时间 = 0.0791秒\n",
-      "  kroB100.tsp: 执行时间 = 0.0874秒\n",
-      "  kroD100.tsp: 执行时间 = 0.0952秒\n",
-      "  kroA100.tsp: 执行时间 = 0.0976秒\n",
-      "  kroC100.tsp: 执行时间 = 0.0923秒\n",
-      "  kroE100.tsp: 执行时间 = 0.0917秒\n",
-      "  eil101.tsp: 执行时间 = 0.0899秒\n",
-      "  lin105.tsp: 执行时间 = 0.0933秒\n",
-      "  pr107.tsp: 执行时间 = 0.0850秒\n",
-      "  pr124.tsp: 执行时间 = 0.1198秒\n",
-      "  bier127.tsp: 执行时间 = 0.1205秒\n",
-      "  ch130.tsp: 执行时间 = 0.1234秒\n",
-      "  pr136.tsp: 执行时间 = 0.1206秒\n",
-      "  gr137.tsp: 执行时间 = 0.1346秒\n",
-      "  pr144.tsp: 执行时间 = 0.1331秒\n",
-      "  kroA150.tsp: 执行时间 = 0.1343秒\n",
-      "  ch150.tsp: 执行时间 = 0.1503秒\n",
-      "  kroB150.tsp: 执行时间 = 0.1425秒\n",
-      "  pr152.tsp: 执行时间 = 0.1372秒\n",
-      "  u159.tsp: 执行时间 = 0.1548秒\n",
-      "  rat195.tsp: 执行时间 = 0.2376秒\n",
-      "  d198.tsp: 执行时间 = 0.2144秒\n",
-      "  kroB200.tsp: 执行时间 = 0.2561秒\n",
-      "  kroA200.tsp: 执行时间 = 0.2057秒\n",
-      "  gr202.tsp: 执行时间 = 0.2131秒\n",
-      "  tsp225.tsp: 执行时间 = 0.2429秒\n",
-      "  ts225.tsp: 执行时间 = 0.2497秒\n",
-      "  pr226.tsp: 执行时间 = 0.2426秒\n",
-      "  gr229.tsp: 执行时间 = 0.2532秒\n",
-      "  gil262.tsp: 执行时间 = 0.3277秒\n",
-      "  pr264.tsp: 执行时间 = 0.3348秒\n",
-      "  a280.tsp: 执行时间 = 0.3710秒\n",
-      "  pr299.tsp: 执行时间 = 0.4082秒\n",
-      "  linhp318.tsp: 执行时间 = 0.5548秒\n",
-      "  lin318.tsp: 执行时间 = 0.4869秒\n",
-      "  rd400.tsp: 执行时间 = 0.7092秒\n",
-      "  fl417.tsp: 执行时间 = 0.7209秒\n",
-      "  gr431.tsp: 执行时间 = 0.8217秒\n",
-      "  pr439.tsp: 执行时间 = 0.4491秒\n",
-      "  pcb442.tsp: 执行时间 = 0.5471秒\n",
-      "  d493.tsp: 执行时间 = 0.4954秒\n",
-      "  att532.tsp: 执行时间 = 0.6501秒\n",
-      "  ali535.tsp: 执行时间 = 0.5881秒\n",
+      "  att48.tsp: 执行时间 = 0.0307秒\n",
+      "  eil51.tsp: 执行时间 = 0.0342秒\n",
+      "  berlin52.tsp: 执行时间 = 0.0442秒\n",
+      "  st70.tsp: 执行时间 = 0.0584秒\n",
+      "  pr76.tsp: 执行时间 = 0.0688秒\n",
+      "  eil76.tsp: 执行时间 = 0.0673秒\n",
+      "  gr96.tsp: 执行时间 = 0.0769秒\n",
+      "  rat99.tsp: 执行时间 = 0.1031秒\n",
+      "  rd100.tsp: 执行时间 = 0.0986秒\n",
+      "  kroB100.tsp: 执行时间 = 0.0981秒\n",
+      "  kroD100.tsp: 执行时间 = 0.0862秒\n",
+      "  kroA100.tsp: 执行时间 = 0.0825秒\n",
+      "  kroC100.tsp: 执行时间 = 0.0842秒\n",
+      "  kroE100.tsp: 执行时间 = 0.0972秒\n",
+      "  eil101.tsp: 执行时间 = 0.0867秒\n",
+      "  lin105.tsp: 执行时间 = 0.0962秒\n",
+      "  pr107.tsp: 执行时间 = 0.1044秒\n",
+      "  pr124.tsp: 执行时间 = 0.1309秒\n",
+      "  bier127.tsp: 执行时间 = 0.1216秒\n",
+      "  ch130.tsp: 执行时间 = 0.1343秒\n",
+      "  pr136.tsp: 执行时间 = 0.1478秒\n",
+      "  gr137.tsp: 执行时间 = 0.1438秒\n",
+      "  pr144.tsp: 执行时间 = 0.1484秒\n",
+      "  kroA150.tsp: 执行时间 = 0.1586秒\n",
+      "  ch150.tsp: 执行时间 = 0.1501秒\n",
+      "  kroB150.tsp: 执行时间 = 0.1559秒\n",
+      "  pr152.tsp: 执行时间 = 0.1499秒\n",
+      "  u159.tsp: 执行时间 = 0.1661秒\n",
+      "  rat195.tsp: 执行时间 = 0.2163秒\n",
+      "  d198.tsp: 执行时间 = 0.2329秒\n",
+      "  kroB200.tsp: 执行时间 = 0.2069秒\n",
+      "  kroA200.tsp: 执行时间 = 0.2339秒\n",
+      "  gr202.tsp: 执行时间 = 0.2186秒\n",
+      "  tsp225.tsp: 执行时间 = 0.2567秒\n",
+      "  ts225.tsp: 执行时间 = 0.2431秒\n",
+      "  pr226.tsp: 执行时间 = 0.3356秒\n",
+      "  gr229.tsp: 执行时间 = 0.2919秒\n",
+      "  gil262.tsp: 执行时间 = 0.3174秒\n",
+      "  pr264.tsp: 执行时间 = 0.3232秒\n",
+      "  a280.tsp: 执行时间 = 0.4066秒\n",
+      "  pr299.tsp: 执行时间 = 0.3982秒\n",
+      "  linhp318.tsp: 执行时间 = 0.4805秒\n",
+      "  lin318.tsp: 执行时间 = 0.4752秒\n",
+      "  rd400.tsp: 执行时间 = 0.6801秒\n",
+      "  fl417.tsp: 执行时间 = 0.7143秒\n",
+      "  gr431.tsp: 执行时间 = 0.7366秒\n",
+      "  pr439.tsp: 执行时间 = 0.7811秒\n",
+      "  pcb442.tsp: 执行时间 = 0.7918秒\n",
+      "  d493.tsp: 执行时间 = 0.9321秒\n",
+      "  att532.tsp: 执行时间 = 1.0641秒\n",
+      "  ali535.tsp: 执行时间 = 1.0862秒\n",
       "  pa561.tsp: 执行时间 = inf秒\n",
-      "  u574.tsp: 执行时间 = 0.7088秒\n",
-      "  rat575.tsp: 执行时间 = 0.6515秒\n",
-      "  p654.tsp: 执行时间 = 0.9786秒\n",
-      "  d657.tsp: 执行时间 = 0.9157秒\n",
-      "  gr666.tsp: 执行时间 = 1.0282秒\n",
-      "  u724.tsp: 执行时间 = 1.0141秒\n",
-      "  rat783.tsp: 执行时间 = 1.1461秒\n",
-      "  dsj1000.tsp: 执行时间 = 1.8257秒\n",
-      "  pr1002.tsp: 执行时间 = 2.8392秒\n",
-      "  u1060.tsp: 执行时间 = 2.6807秒\n",
-      "  vm1084.tsp: 执行时间 = 2.6446秒\n",
-      "  pcb1173.tsp: 执行时间 = 2.8048秒\n",
-      "  d1291.tsp: 执行时间 = 2.8732秒\n",
-      "  rl1304.tsp: 执行时间 = 3.2245秒\n",
-      "  rl1323.tsp: 执行时间 = 3.0296秒\n",
-      "  nrw1379.tsp: 执行时间 = 3.6320秒\n",
-      "  fl1400.tsp: 执行时间 = 3.4932秒\n",
-      "  u1432.tsp: 执行时间 = 3.5985秒\n",
+      "  u574.tsp: 执行时间 = 1.2306秒\n",
+      "  rat575.tsp: 执行时间 = 1.2574秒\n",
+      "  p654.tsp: 执行时间 = 1.5922秒\n",
+      "  d657.tsp: 执行时间 = 1.7656秒\n",
+      "  gr666.tsp: 执行时间 = 1.6598秒\n",
+      "  u724.tsp: 执行时间 = 1.9141秒\n",
+      "  rat783.tsp: 执行时间 = 2.3729秒\n",
+      "  dsj1000.tsp: 执行时间 = 3.4452秒\n",
+      "  pr1002.tsp: 执行时间 = 2.4444秒\n",
+      "  u1060.tsp: 执行时间 = 1.9743秒\n",
+      "  vm1084.tsp: 执行时间 = 2.3008秒\n",
+      "  pcb1173.tsp: 执行时间 = 2.6624秒\n",
+      "  d1291.tsp: 执行时间 = 3.7137秒\n",
+      "  rl1304.tsp: 执行时间 = 3.0462秒\n",
+      "  rl1323.tsp: 执行时间 = 3.1830秒\n",
+      "  nrw1379.tsp: 执行时间 = 3.4999秒\n",
+      "  fl1400.tsp: 执行时间 = 3.8870秒\n",
+      "  u1432.tsp: 执行时间 = 3.8517秒\n",
       "\n",
       "AAD-TSP:\n",
-      "  burma14.tsp: 路径长度 = 30.88\n",
-      "  ulysses16.tsp: 路径长度 = 74.20\n",
-      "  ulysses22.tsp: 路径长度 = 76.13\n",
+      "  burma14.tsp: 路径长度 = 31.23\n",
+      "  ulysses16.tsp: 路径长度 = 73.99\n",
+      "  ulysses22.tsp: 路径长度 = 76.89\n",
       "  dantzig42.tsp: 路径长度 = inf\n",
-      "  att48.tsp: 路径长度 = 35594.44\n",
+      "  att48.tsp: 路径长度 = 35738.05\n",
       "  eil51.tsp: 路径长度 = 465.91\n",
-      "  berlin52.tsp: 路径长度 = 8383.59\n",
+      "  berlin52.tsp: 路径长度 = 8178.40\n",
       "  st70.tsp: 路径长度 = 753.15\n",
-      "  pr76.tsp: 路径长度 = 113661.65\n",
+      "  pr76.tsp: 路径长度 = 117831.22\n",
       "  eil76.tsp: 路径长度 = 622.71\n",
       "  gr96.tsp: 路径长度 = 623.53\n",
       "  rat99.tsp: 路径长度 = 1377.07\n",
       "  rd100.tsp: 路径长度 = 8864.57\n",
-      "  kroB100.tsp: 路径长度 = 25613.43\n",
-      "  kroD100.tsp: 路径长度 = 24720.72\n",
-      "  kroA100.tsp: 路径长度 = 23078.70\n",
-      "  kroC100.tsp: 路径长度 = 23205.07\n",
+      "  kroB100.tsp: 路径长度 = 25392.46\n",
+      "  kroD100.tsp: 路径长度 = 24565.25\n",
+      "  kroA100.tsp: 路径长度 = 22957.15\n",
+      "  kroC100.tsp: 路径长度 = 23253.25\n",
       "  kroE100.tsp: 路径长度 = 24382.95\n",
       "  eil101.tsp: 路径长度 = 702.70\n",
-      "  lin105.tsp: 路径长度 = 18092.45\n",
-      "  pr107.tsp: 路径长度 = 45487.66\n",
-      "  pr124.tsp: 路径长度 = 60665.35\n",
-      "  bier127.tsp: 路径长度 = 122761.77\n",
+      "  lin105.tsp: 路径长度 = 18371.79\n",
+      "  pr107.tsp: 路径长度 = 44905.53\n",
+      "  pr124.tsp: 路径长度 = 63601.53\n",
+      "  bier127.tsp: 路径长度 = 123202.55\n",
       "  ch130.tsp: 路径长度 = 7093.18\n",
-      "  pr136.tsp: 路径长度 = 110107.30\n",
+      "  pr136.tsp: 路径长度 = 110347.07\n",
       "  gr137.tsp: 路径长度 = 849.98\n",
-      "  pr144.tsp: 路径长度 = 61399.21\n",
-      "  kroA150.tsp: 路径长度 = 28613.32\n",
+      "  pr144.tsp: 路径长度 = 61214.65\n",
+      "  kroA150.tsp: 路径长度 = 28767.65\n",
       "  ch150.tsp: 路径长度 = 7161.32\n",
-      "  kroB150.tsp: 路径长度 = 28339.58\n",
-      "  pr152.tsp: 路径长度 = 80000.73\n",
-      "  u159.tsp: 路径长度 = 50463.07\n",
+      "  kroB150.tsp: 路径长度 = 28181.08\n",
+      "  pr152.tsp: 路径长度 = 80448.65\n",
+      "  u159.tsp: 路径长度 = 50416.01\n",
       "  rat195.tsp: 路径长度 = 2490.60\n",
       "  d198.tsp: 路径长度 = 17340.94\n",
-      "  kroB200.tsp: 路径长度 = 34175.92\n",
-      "  kroA200.tsp: 路径长度 = 30478.90\n",
+      "  kroB200.tsp: 路径长度 = 34372.39\n",
+      "  kroA200.tsp: 路径长度 = 30701.99\n",
       "  gr202.tsp: 路径长度 = 529.30\n",
       "  tsp225.tsp: 路径长度 = 4169.09\n",
       "  ts225.tsp: 路径长度 = 139697.02\n",
@@ -2359,98 +2359,98 @@
       "  att532.tsp: 路径长度 = 99028.54\n",
       "  ali535.tsp: 路径长度 = 2269.30\n",
       "  pa561.tsp: 路径长度 = inf\n",
-      "  u574.tsp: 路径长度 = 39154.50\n",
+      "  u574.tsp: 路径长度 = 39340.35\n",
       "  rat575.tsp: 路径长度 = 7398.48\n",
       "  p654.tsp: 路径长度 = 38249.53\n",
       "  d657.tsp: 路径长度 = 54801.59\n",
       "  gr666.tsp: 路径长度 = 3507.73\n",
-      "  u724.tsp: 路径长度 = 47256.49\n",
+      "  u724.tsp: 路径长度 = 47108.98\n",
       "  rat783.tsp: 路径长度 = 9468.73\n",
       "  dsj1000.tsp: 路径长度 = 21147745.60\n",
-      "  pr1002.tsp: 路径长度 = 278851.88\n",
+      "  pr1002.tsp: 路径长度 = 278832.89\n",
       "  u1060.tsp: 路径长度 = 241924.19\n",
-      "  vm1084.tsp: 路径长度 = 263604.55\n",
-      "  pcb1173.tsp: 路径长度 = 62453.05\n",
+      "  vm1084.tsp: 路径长度 = 262266.88\n",
+      "  pcb1173.tsp: 路径长度 = 62709.99\n",
       "  d1291.tsp: 路径长度 = 55389.49\n",
-      "  rl1304.tsp: 路径长度 = 284242.81\n",
+      "  rl1304.tsp: 路径长度 = 284284.10\n",
       "  rl1323.tsp: 路径长度 = 299654.18\n",
       "  nrw1379.tsp: 路径长度 = 61838.87\n",
       "  fl1400.tsp: 路径长度 = 22420.49\n",
       "  u1432.tsp: 路径长度 = 167338.88\n",
-      "  burma14.tsp: 执行时间 = 0.0212秒\n",
-      "  ulysses16.tsp: 执行时间 = 0.0254秒\n",
-      "  ulysses22.tsp: 执行时间 = 0.0340秒\n",
+      "  burma14.tsp: 执行时间 = 0.0206秒\n",
+      "  ulysses16.tsp: 执行时间 = 0.0241秒\n",
+      "  ulysses22.tsp: 执行时间 = 0.0349秒\n",
       "  dantzig42.tsp: 执行时间 = inf秒\n",
-      "  att48.tsp: 执行时间 = 0.0693秒\n",
-      "  eil51.tsp: 执行时间 = 0.0755秒\n",
-      "  berlin52.tsp: 执行时间 = 0.0881秒\n",
-      "  st70.tsp: 执行时间 = 0.1139秒\n",
-      "  pr76.tsp: 执行时间 = 0.1455秒\n",
-      "  eil76.tsp: 执行时间 = 0.1086秒\n",
-      "  gr96.tsp: 执行时间 = 0.2177秒\n",
-      "  rat99.tsp: 执行时间 = 0.1861秒\n",
-      "  rd100.tsp: 执行时间 = 0.1733秒\n",
-      "  kroB100.tsp: 执行时间 = 0.1947秒\n",
-      "  kroD100.tsp: 执行时间 = 0.1958秒\n",
-      "  kroA100.tsp: 执行时间 = 0.2082秒\n",
-      "  kroC100.tsp: 执行时间 = 0.1707秒\n",
-      "  kroE100.tsp: 执行时间 = 0.1582秒\n",
-      "  eil101.tsp: 执行时间 = 0.2089秒\n",
-      "  lin105.tsp: 执行时间 = 0.2248秒\n",
-      "  pr107.tsp: 执行时间 = 0.1293秒\n",
-      "  pr124.tsp: 执行时间 = 0.2008秒\n",
-      "  bier127.tsp: 执行时间 = 0.2334秒\n",
-      "  ch130.tsp: 执行时间 = 0.2159秒\n",
-      "  pr136.tsp: 执行时间 = 0.2525秒\n",
-      "  gr137.tsp: 执行时间 = 0.4666秒\n",
-      "  pr144.tsp: 执行时间 = 0.1867秒\n",
-      "  kroA150.tsp: 执行时间 = 0.3946秒\n",
-      "  ch150.tsp: 执行时间 = 0.4033秒\n",
-      "  kroB150.tsp: 执行时间 = 0.4610秒\n",
-      "  pr152.tsp: 执行时间 = 0.3713秒\n",
-      "  u159.tsp: 执行时间 = 0.3393秒\n",
-      "  rat195.tsp: 执行时间 = 0.5750秒\n",
-      "  d198.tsp: 执行时间 = 0.5679秒\n",
-      "  kroB200.tsp: 执行时间 = 0.6496秒\n",
-      "  kroA200.tsp: 执行时间 = 0.9275秒\n",
-      "  gr202.tsp: 执行时间 = 0.8817秒\n",
-      "  tsp225.tsp: 执行时间 = 1.1539秒\n",
-      "  ts225.tsp: 执行时间 = 0.7152秒\n",
-      "  pr226.tsp: 执行时间 = 0.5740秒\n",
-      "  gr229.tsp: 执行时间 = 0.9931秒\n",
-      "  gil262.tsp: 执行时间 = 1.8501秒\n",
-      "  pr264.tsp: 执行时间 = 0.7189秒\n",
-      "  a280.tsp: 执行时间 = 1.2460秒\n",
-      "  pr299.tsp: 执行时间 = 1.5777秒\n",
-      "  linhp318.tsp: 执行时间 = 2.2579秒\n",
-      "  lin318.tsp: 执行时间 = 2.2018秒\n",
-      "  rd400.tsp: 执行时间 = 4.5916秒\n",
-      "  fl417.tsp: 执行时间 = 7.5823秒\n",
-      "  gr431.tsp: 执行时间 = 5.4522秒\n",
-      "  pr439.tsp: 执行时间 = 2.5368秒\n",
-      "  pcb442.tsp: 执行时间 = 2.7801秒\n",
-      "  d493.tsp: 执行时间 = 4.9482秒\n",
-      "  att532.tsp: 执行时间 = 6.3833秒\n",
-      "  ali535.tsp: 执行时间 = 8.2581秒\n",
+      "  att48.tsp: 执行时间 = 0.0671秒\n",
+      "  eil51.tsp: 执行时间 = 0.0815秒\n",
+      "  berlin52.tsp: 执行时间 = 0.0888秒\n",
+      "  st70.tsp: 执行时间 = 0.1202秒\n",
+      "  pr76.tsp: 执行时间 = 0.1371秒\n",
+      "  eil76.tsp: 执行时间 = 0.1221秒\n",
+      "  gr96.tsp: 执行时间 = 0.2633秒\n",
+      "  rat99.tsp: 执行时间 = 0.1965秒\n",
+      "  rd100.tsp: 执行时间 = 0.2223秒\n",
+      "  kroB100.tsp: 执行时间 = 0.2087秒\n",
+      "  kroD100.tsp: 执行时间 = 0.1775秒\n",
+      "  kroA100.tsp: 执行时间 = 0.1498秒\n",
+      "  kroC100.tsp: 执行时间 = 0.1798秒\n",
+      "  kroE100.tsp: 执行时间 = 0.1961秒\n",
+      "  eil101.tsp: 执行时间 = 0.2088秒\n",
+      "  lin105.tsp: 执行时间 = 0.1928秒\n",
+      "  pr107.tsp: 执行时间 = 0.1547秒\n",
+      "  pr124.tsp: 执行时间 = 0.1921秒\n",
+      "  bier127.tsp: 执行时间 = 0.2196秒\n",
+      "  ch130.tsp: 执行时间 = 0.2306秒\n",
+      "  pr136.tsp: 执行时间 = 0.2450秒\n",
+      "  gr137.tsp: 执行时间 = 0.5256秒\n",
+      "  pr144.tsp: 执行时间 = 0.2336秒\n",
+      "  kroA150.tsp: 执行时间 = 0.4204秒\n",
+      "  ch150.tsp: 执行时间 = 0.3711秒\n",
+      "  kroB150.tsp: 执行时间 = 0.4201秒\n",
+      "  pr152.tsp: 执行时间 = 0.2910秒\n",
+      "  u159.tsp: 执行时间 = 0.3241秒\n",
+      "  rat195.tsp: 执行时间 = 0.5768秒\n",
+      "  d198.tsp: 执行时间 = 0.6631秒\n",
+      "  kroB200.tsp: 执行时间 = 0.7495秒\n",
+      "  kroA200.tsp: 执行时间 = 0.8138秒\n",
+      "  gr202.tsp: 执行时间 = 0.9231秒\n",
+      "  tsp225.tsp: 执行时间 = 1.2099秒\n",
+      "  ts225.tsp: 执行时间 = 0.6736秒\n",
+      "  pr226.tsp: 执行时间 = 0.5864秒\n",
+      "  gr229.tsp: 执行时间 = 1.0688秒\n",
+      "  gil262.tsp: 执行时间 = 1.6125秒\n",
+      "  pr264.tsp: 执行时间 = 0.7822秒\n",
+      "  a280.tsp: 执行时间 = 1.4158秒\n",
+      "  pr299.tsp: 执行时间 = 1.5654秒\n",
+      "  linhp318.tsp: 执行时间 = 2.2263秒\n",
+      "  lin318.tsp: 执行时间 = 2.0872秒\n",
+      "  rd400.tsp: 执行时间 = 4.1070秒\n",
+      "  fl417.tsp: 执行时间 = 7.6544秒\n",
+      "  gr431.tsp: 执行时间 = 5.0698秒\n",
+      "  pr439.tsp: 执行时间 = 4.3660秒\n",
+      "  pcb442.tsp: 执行时间 = 4.3208秒\n",
+      "  d493.tsp: 执行时间 = 7.6122秒\n",
+      "  att532.tsp: 执行时间 = 9.7291秒\n",
+      "  ali535.tsp: 执行时间 = 12.8892秒\n",
       "  pa561.tsp: 执行时间 = inf秒\n",
-      "  u574.tsp: 执行时间 = 8.8392秒\n",
-      "  rat575.tsp: 执行时间 = 6.0627秒\n",
-      "  p654.tsp: 执行时间 = 12.9592秒\n",
-      "  d657.tsp: 执行时间 = 9.9684秒\n",
-      "  gr666.tsp: 执行时间 = 19.6285秒\n",
-      "  u724.tsp: 执行时间 = 13.3697秒\n",
-      "  rat783.tsp: 执行时间 = 22.3859秒\n",
-      "  dsj1000.tsp: 执行时间 = 59.6672秒\n",
-      "  pr1002.tsp: 执行时间 = 41.2541秒\n",
-      "  u1060.tsp: 执行时间 = 49.7501秒\n",
-      "  vm1084.tsp: 执行时间 = 35.7943秒\n",
-      "  pcb1173.tsp: 执行时间 = 45.7643秒\n",
-      "  d1291.tsp: 执行时间 = 17.4007秒\n",
-      "  rl1304.tsp: 执行时间 = 49.8281秒\n",
-      "  rl1323.tsp: 执行时间 = 44.1189秒\n",
-      "  nrw1379.tsp: 执行时间 = 96.8080秒\n",
-      "  fl1400.tsp: 执行时间 = 265.7287秒\n",
-      "  u1432.tsp: 执行时间 = 79.1341秒\n",
+      "  u574.tsp: 执行时间 = 14.3463秒\n",
+      "  rat575.tsp: 执行时间 = 10.7307秒\n",
+      "  p654.tsp: 执行时间 = 21.2350秒\n",
+      "  d657.tsp: 执行时间 = 17.0557秒\n",
+      "  gr666.tsp: 执行时间 = 29.4371秒\n",
+      "  u724.tsp: 执行时间 = 22.5706秒\n",
+      "  rat783.tsp: 执行时间 = 40.4463秒\n",
+      "  dsj1000.tsp: 执行时间 = 91.5279秒\n",
+      "  pr1002.tsp: 执行时间 = 39.5357秒\n",
+      "  u1060.tsp: 执行时间 = 46.9793秒\n",
+      "  vm1084.tsp: 执行时间 = 36.6202秒\n",
+      "  pcb1173.tsp: 执行时间 = 47.8099秒\n",
+      "  d1291.tsp: 执行时间 = 17.3619秒\n",
+      "  rl1304.tsp: 执行时间 = 54.3530秒\n",
+      "  rl1323.tsp: 执行时间 = 45.0123秒\n",
+      "  nrw1379.tsp: 执行时间 = 100.5585秒\n",
+      "  fl1400.tsp: 执行时间 = 205.7018秒\n",
+      "  u1432.tsp: 执行时间 = 85.9519秒\n",
       "\n",
       "MEoH-TSP:\n",
       "  burma14.tsp: 路径长度 = 38.80\n",
@@ -2527,90 +2527,90 @@
       "  nrw1379.tsp: 路径长度 = 68362.91\n",
       "  fl1400.tsp: 路径长度 = 23757.04\n",
       "  u1432.tsp: 路径长度 = 173489.17\n",
-      "  burma14.tsp: 执行时间 = 0.0010秒\n",
-      "  ulysses16.tsp: 执行时间 = 0.0012秒\n",
+      "  burma14.tsp: 执行时间 = 0.0013秒\n",
+      "  ulysses16.tsp: 执行时间 = 0.0009秒\n",
       "  ulysses22.tsp: 执行时间 = 0.0012秒\n",
       "  dantzig42.tsp: 执行时间 = inf秒\n",
-      "  att48.tsp: 执行时间 = 0.0033秒\n",
-      "  eil51.tsp: 执行时间 = 0.0032秒\n",
-      "  berlin52.tsp: 执行时间 = 0.0030秒\n",
-      "  st70.tsp: 执行时间 = 0.0036秒\n",
-      "  pr76.tsp: 执行时间 = 0.0047秒\n",
-      "  eil76.tsp: 执行时间 = 0.0040秒\n",
-      "  gr96.tsp: 执行时间 = 0.0063秒\n",
-      "  rat99.tsp: 执行时间 = 0.0046秒\n",
-      "  rd100.tsp: 执行时间 = 0.0046秒\n",
-      "  kroB100.tsp: 执行时间 = 0.0046秒\n",
-      "  kroD100.tsp: 执行时间 = 0.0036秒\n",
-      "  kroA100.tsp: 执行时间 = 0.0069秒\n",
-      "  kroC100.tsp: 执行时间 = 0.0060秒\n",
-      "  kroE100.tsp: 执行时间 = 0.0053秒\n",
-      "  eil101.tsp: 执行时间 = 0.0063秒\n",
-      "  lin105.tsp: 执行时间 = 0.0086秒\n",
-      "  pr107.tsp: 执行时间 = 0.0042秒\n",
-      "  pr124.tsp: 执行时间 = 0.0061秒\n",
-      "  bier127.tsp: 执行时间 = 0.0059秒\n",
-      "  ch130.tsp: 执行时间 = 0.0068秒\n",
-      "  pr136.tsp: 执行时间 = 0.0069秒\n",
-      "  gr137.tsp: 执行时间 = 0.0077秒\n",
-      "  pr144.tsp: 执行时间 = 0.0056秒\n",
-      "  kroA150.tsp: 执行时间 = 0.0073秒\n",
-      "  ch150.tsp: 执行时间 = 0.0069秒\n",
-      "  kroB150.tsp: 执行时间 = 0.0083秒\n",
-      "  pr152.tsp: 执行时间 = 0.0107秒\n",
-      "  u159.tsp: 执行时间 = 0.0089秒\n",
-      "  rat195.tsp: 执行时间 = 0.0107秒\n",
-      "  d198.tsp: 执行时间 = 0.0084秒\n",
-      "  kroB200.tsp: 执行时间 = 0.0090秒\n",
-      "  kroA200.tsp: 执行时间 = 0.0118秒\n",
-      "  gr202.tsp: 执行时间 = 0.0115秒\n",
-      "  tsp225.tsp: 执行时间 = 0.0096秒\n",
-      "  ts225.tsp: 执行时间 = 0.0114秒\n",
-      "  pr226.tsp: 执行时间 = 0.0107秒\n",
-      "  gr229.tsp: 执行时间 = 0.0099秒\n",
-      "  gil262.tsp: 执行时间 = 0.0154秒\n",
-      "  pr264.tsp: 执行时间 = 0.0059秒\n",
-      "  a280.tsp: 执行时间 = 0.0127秒\n",
-      "  pr299.tsp: 执行时间 = 0.0178秒\n",
-      "  linhp318.tsp: 执行时间 = 0.0173秒\n",
-      "  lin318.tsp: 执行时间 = 0.0220秒\n",
-      "  rd400.tsp: 执行时间 = 0.0297秒\n",
-      "  fl417.tsp: 执行时间 = 0.0236秒\n",
-      "  gr431.tsp: 执行时间 = 0.0250秒\n",
-      "  pr439.tsp: 执行时间 = 0.0130秒\n",
-      "  pcb442.tsp: 执行时间 = 0.0156秒\n",
-      "  d493.tsp: 执行时间 = 0.0196秒\n",
-      "  att532.tsp: 执行时间 = 0.0229秒\n",
-      "  ali535.tsp: 执行时间 = 0.0202秒\n",
+      "  att48.tsp: 执行时间 = 0.0029秒\n",
+      "  eil51.tsp: 执行时间 = 0.0030秒\n",
+      "  berlin52.tsp: 执行时间 = 0.0040秒\n",
+      "  st70.tsp: 执行时间 = 0.0047秒\n",
+      "  pr76.tsp: 执行时间 = 0.0046秒\n",
+      "  eil76.tsp: 执行时间 = 0.0046秒\n",
+      "  gr96.tsp: 执行时间 = 0.0065秒\n",
+      "  rat99.tsp: 执行时间 = 0.0057秒\n",
+      "  rd100.tsp: 执行时间 = 0.0058秒\n",
+      "  kroB100.tsp: 执行时间 = 0.0033秒\n",
+      "  kroD100.tsp: 执行时间 = 0.0061秒\n",
+      "  kroA100.tsp: 执行时间 = 0.0061秒\n",
+      "  kroC100.tsp: 执行时间 = 0.0049秒\n",
+      "  kroE100.tsp: 执行时间 = 0.0061秒\n",
+      "  eil101.tsp: 执行时间 = 0.0051秒\n",
+      "  lin105.tsp: 执行时间 = 0.0026秒\n",
+      "  pr107.tsp: 执行时间 = 0.0060秒\n",
+      "  pr124.tsp: 执行时间 = 0.0054秒\n",
+      "  bier127.tsp: 执行时间 = 0.0069秒\n",
+      "  ch130.tsp: 执行时间 = 0.0070秒\n",
+      "  pr136.tsp: 执行时间 = 0.0074秒\n",
+      "  gr137.tsp: 执行时间 = 0.0085秒\n",
+      "  pr144.tsp: 执行时间 = 0.0070秒\n",
+      "  kroA150.tsp: 执行时间 = 0.0089秒\n",
+      "  ch150.tsp: 执行时间 = 0.0087秒\n",
+      "  kroB150.tsp: 执行时间 = 0.0090秒\n",
+      "  pr152.tsp: 执行时间 = 0.0070秒\n",
+      "  u159.tsp: 执行时间 = 0.0079秒\n",
+      "  rat195.tsp: 执行时间 = 0.0116秒\n",
+      "  d198.tsp: 执行时间 = 0.0113秒\n",
+      "  kroB200.tsp: 执行时间 = 0.0099秒\n",
+      "  kroA200.tsp: 执行时间 = 0.0106秒\n",
+      "  gr202.tsp: 执行时间 = 0.0095秒\n",
+      "  tsp225.tsp: 执行时间 = 0.0128秒\n",
+      "  ts225.tsp: 执行时间 = 0.0116秒\n",
+      "  pr226.tsp: 执行时间 = 0.0140秒\n",
+      "  gr229.tsp: 执行时间 = 0.0159秒\n",
+      "  gil262.tsp: 执行时间 = 0.0139秒\n",
+      "  pr264.tsp: 执行时间 = 0.0159秒\n",
+      "  a280.tsp: 执行时间 = 0.0153秒\n",
+      "  pr299.tsp: 执行时间 = 0.0157秒\n",
+      "  linhp318.tsp: 执行时间 = 0.0260秒\n",
+      "  lin318.tsp: 执行时间 = 0.0184秒\n",
+      "  rd400.tsp: 执行时间 = 0.0254秒\n",
+      "  fl417.tsp: 执行时间 = 0.0244秒\n",
+      "  gr431.tsp: 执行时间 = 0.0273秒\n",
+      "  pr439.tsp: 执行时间 = 0.0269秒\n",
+      "  pcb442.tsp: 执行时间 = 0.0248秒\n",
+      "  d493.tsp: 执行时间 = 0.0316秒\n",
+      "  att532.tsp: 执行时间 = 0.0439秒\n",
+      "  ali535.tsp: 执行时间 = 0.0354秒\n",
       "  pa561.tsp: 执行时间 = inf秒\n",
-      "  u574.tsp: 执行时间 = 0.0193秒\n",
-      "  rat575.tsp: 执行时间 = 0.0200秒\n",
-      "  p654.tsp: 执行时间 = 0.0310秒\n",
-      "  d657.tsp: 执行时间 = 0.0275秒\n",
-      "  gr666.tsp: 执行时间 = 0.0308秒\n",
-      "  u724.tsp: 执行时间 = 0.0300秒\n",
-      "  rat783.tsp: 执行时间 = 0.0357秒\n",
-      "  dsj1000.tsp: 执行时间 = 0.0577秒\n",
-      "  pr1002.tsp: 执行时间 = 0.0629秒\n",
-      "  u1060.tsp: 执行时间 = 0.0943秒\n",
-      "  vm1084.tsp: 执行时间 = 0.0649秒\n",
-      "  pcb1173.tsp: 执行时间 = 0.0674秒\n",
-      "  d1291.tsp: 执行时间 = 0.0787秒\n",
-      "  rl1304.tsp: 执行时间 = 0.1418秒\n",
-      "  rl1323.tsp: 执行时间 = 0.0974秒\n",
-      "  nrw1379.tsp: 执行时间 = 0.1103秒\n",
-      "  fl1400.tsp: 执行时间 = 0.1604秒\n",
-      "  u1432.tsp: 执行时间 = 0.0944秒\n",
+      "  u574.tsp: 执行时间 = 0.0401秒\n",
+      "  rat575.tsp: 执行时间 = 0.0477秒\n",
+      "  p654.tsp: 执行时间 = 0.0448秒\n",
+      "  d657.tsp: 执行时间 = 0.0487秒\n",
+      "  gr666.tsp: 执行时间 = 0.0552秒\n",
+      "  u724.tsp: 执行时间 = 0.0653秒\n",
+      "  rat783.tsp: 执行时间 = 0.0693秒\n",
+      "  dsj1000.tsp: 执行时间 = 0.0580秒\n",
+      "  pr1002.tsp: 执行时间 = 0.0474秒\n",
+      "  u1060.tsp: 执行时间 = 0.1422秒\n",
+      "  vm1084.tsp: 执行时间 = 0.0652秒\n",
+      "  pcb1173.tsp: 执行时间 = 0.0695秒\n",
+      "  d1291.tsp: 执行时间 = 0.0801秒\n",
+      "  rl1304.tsp: 执行时间 = 0.1450秒\n",
+      "  rl1323.tsp: 执行时间 = 0.0908秒\n",
+      "  nrw1379.tsp: 执行时间 = 0.1221秒\n",
+      "  fl1400.tsp: 执行时间 = 0.0907秒\n",
+      "  u1432.tsp: 执行时间 = 0.1026秒\n",
       "\n",
       "各算法在不同实例上的路径长度:\n",
       "                贪心算法      最近邻算法        插入法    EoH-TSP    AAD-TSP   MEoH-TSP\n",
-      "burma14        38.69      38.69      32.44      38.69      30.88      38.80\n",
-      "ulysses16     104.73     104.73      79.39      88.25      74.20     104.65\n",
-      "ulysses22      89.64      89.64      76.99      82.21      76.13      91.92\n",
+      "burma14        38.69      38.69      32.44      38.69      31.23      38.80\n",
+      "ulysses16     104.73     104.73      79.39      76.87      73.99     104.65\n",
+      "ulysses22      89.64      89.64      76.99      89.64      76.89      91.92\n",
       "dantzig42       0.00       0.00        inf        inf        inf        inf\n",
-      "att48       40526.42   40526.42   37314.09   40526.42   35594.44   37686.87\n",
+      "att48       40526.42   40526.42   37314.09   40526.42   35738.05   37686.87\n",
       "...              ...        ...        ...        ...        ...        ...\n",
-      "rl1304     339797.47  339797.47  314295.61  335160.35  284242.81  303550.70\n",
+      "rl1304     339797.47  339797.47  314295.61  335160.35  284284.10  303550.70\n",
       "rl1323     332094.97  332094.97  341512.46  331159.20  299654.18  334237.62\n",
       "nrw1379     70015.46   70015.46   66216.21   69794.61   61838.87   68362.91\n",
       "fl1400      26971.88   26971.88   22955.32   27057.04   22420.49   23757.04\n",
@@ -2620,17 +2620,17 @@
       "\n",
       "各算法在不同实例上的运行时长:\n",
       "             贪心算法   最近邻算法       插入法  EoH-TSP   AAD-TSP  MEoH-TSP\n",
-      "burma14    0.0001  0.0000    0.0010   0.0136    0.0212    0.0010\n",
-      "ulysses16  0.0000  0.0000    0.0004   0.0113    0.0254    0.0012\n",
-      "ulysses22  0.0001  0.0001    0.0011   0.0144    0.0340    0.0012\n",
+      "burma14    0.0000  0.0000    0.0004   0.0120    0.0206    0.0013\n",
+      "ulysses16  0.0000  0.0000    0.0007   0.0099    0.0241    0.0009\n",
+      "ulysses22  0.0000  0.0001    0.0010   0.0160    0.0349    0.0012\n",
       "dantzig42  0.0000  0.0000       inf      inf       inf       inf\n",
-      "att48      0.0003  0.0003    0.0112   0.0363    0.0693    0.0033\n",
+      "att48      0.0003  0.0002    0.0124   0.0307    0.0671    0.0029\n",
       "...           ...     ...       ...      ...       ...       ...\n",
-      "rl1304     0.0839  0.0824  130.1252   3.2245   49.8281    0.1418\n",
-      "rl1323     0.0859  0.0859  129.8820   3.0296   44.1189    0.0974\n",
-      "nrw1379    0.1045  0.1040  158.2882   3.6320   96.8080    0.1103\n",
-      "fl1400     0.1030  0.1028  186.6609   3.4932  265.7287    0.1604\n",
-      "u1432      0.2142  0.1910  212.7076   3.5985   79.1341    0.0944\n",
+      "rl1304     0.1415  0.1519  132.5021   3.0462   54.3530    0.1450\n",
+      "rl1323     0.0873  0.0857  194.6513   3.1830   45.0123    0.0908\n",
+      "nrw1379    0.0994  0.1029  161.1092   3.4999  100.5585    0.1221\n",
+      "fl1400     0.1201  0.1193  163.7658   3.8870  205.7018    0.0907\n",
+      "u1432      0.1072  0.1022  162.7644   3.8517   85.9519    0.1026\n",
       "\n",
       "[74 rows x 6 columns]\n"
      ]
@@ -2716,7 +2716,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -2726,35 +2726,35 @@
       "\n",
       "各算法在不同实例上的路径长度:\n",
       "                贪心算法      最近邻算法        插入法    EoH-TSP    AAD-TSP   MEoH-TSP\n",
-      "burma14        38.69      38.69      32.44      38.69      30.88      38.80\n",
-      "ulysses16     104.73     104.73      79.39      88.25      74.20     104.65\n",
-      "ulysses22      89.64      89.64      76.99      82.21      76.13      91.92\n",
-      "dantzig42       0.00       0.00        inf        inf        inf        inf\n",
-      "att48       40526.42   40526.42   37314.09   40526.42   35594.44   37686.87\n",
+      "burma14        38.69      38.69      32.44      38.69      31.23      38.80\n",
+      "ulysses16     104.73     104.73      79.39      76.87      73.99     104.65\n",
+      "ulysses22      89.64      89.64      76.99      89.64      76.89      91.92\n",
+      "att48       40526.42   40526.42   37314.09   40526.42   35738.05   37686.87\n",
+      "eil51         513.61     513.61     496.25     513.61     465.91     458.95\n",
       "...              ...        ...        ...        ...        ...        ...\n",
-      "rl1304     339797.47  339797.47  314295.61  335160.35  284242.81  303550.70\n",
+      "rl1304     339797.47  339797.47  314295.61  335160.35  284284.10  303550.70\n",
       "rl1323     332094.97  332094.97  341512.46  331159.20  299654.18  334237.62\n",
       "nrw1379     70015.46   70015.46   66216.21   69794.61   61838.87   68362.91\n",
       "fl1400      26971.88   26971.88   22955.32   27057.04   22420.49   23757.04\n",
       "u1432      188815.01  188815.01  171110.62  196453.25  167338.88  173489.17\n",
       "\n",
-      "[74 rows x 6 columns]\n",
+      "[72 rows x 6 columns]\n",
       "\n",
       "各算法在不同实例上的运行时长:\n",
       "             贪心算法   最近邻算法       插入法  EoH-TSP   AAD-TSP  MEoH-TSP\n",
-      "burma14    0.0001  0.0000    0.0010   0.0136    0.0212    0.0010\n",
-      "ulysses16  0.0000  0.0000    0.0004   0.0113    0.0254    0.0012\n",
-      "ulysses22  0.0001  0.0001    0.0011   0.0144    0.0340    0.0012\n",
-      "dantzig42  0.0000  0.0000       inf      inf       inf       inf\n",
-      "att48      0.0003  0.0003    0.0112   0.0363    0.0693    0.0033\n",
+      "burma14    0.0000  0.0000    0.0004   0.0120    0.0206    0.0013\n",
+      "ulysses16  0.0000  0.0000    0.0007   0.0099    0.0241    0.0009\n",
+      "ulysses22  0.0000  0.0001    0.0010   0.0160    0.0349    0.0012\n",
+      "att48      0.0003  0.0002    0.0124   0.0307    0.0671    0.0029\n",
+      "eil51      0.0005  0.0004    0.0146   0.0342    0.0815    0.0030\n",
       "...           ...     ...       ...      ...       ...       ...\n",
-      "rl1304     0.0839  0.0824  130.1252   3.2245   49.8281    0.1418\n",
-      "rl1323     0.0859  0.0859  129.8820   3.0296   44.1189    0.0974\n",
-      "nrw1379    0.1045  0.1040  158.2882   3.6320   96.8080    0.1103\n",
-      "fl1400     0.1030  0.1028  186.6609   3.4932  265.7287    0.1604\n",
-      "u1432      0.2142  0.1910  212.7076   3.5985   79.1341    0.0944\n",
+      "rl1304     0.1415  0.1519  132.5021   3.0462   54.3530    0.1450\n",
+      "rl1323     0.0873  0.0857  194.6513   3.1830   45.0123    0.0908\n",
+      "nrw1379    0.0994  0.1029  161.1092   3.4999  100.5585    0.1221\n",
+      "fl1400     0.1201  0.1193  163.7658   3.8870  205.7018    0.0907\n",
+      "u1432      0.1072  0.1022  162.7644   3.8517   85.9519    0.1026\n",
       "\n",
-      "[74 rows x 6 columns]\n"
+      "[72 rows x 6 columns]\n"
      ]
     }
    ],
@@ -2767,6 +2767,10 @@
     "df_results = df_results.iloc[temp_results_idx.argsort()]\n",
     "df_time = df_time.iloc[temp_time_idx.argsort()]\n",
     "\n",
+    "# 删掉包含inf的行\n",
+    "df_results = df_results[~df_results.isin([float('inf')]).any(axis=1)]\n",
+    "df_time = df_time[~df_time.isin([float('inf')]).any(axis=1)]\n",
+    "\n",
     "# 打印结果表格\n",
     "print(\"\\n各算法在不同实例上的路径长度:\")\n",
     "print(df_results.round(2))  # 路径长度保留2位小数\n",
@@ -2777,7 +2781,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -2788,10 +2792,10 @@
       "各算法在不同实例上的排名:\n",
       "           贪心算法  最近邻算法  插入法  EoH-TSP  AAD-TSP  MEoH-TSP\n",
       "burma14       3      3    2        3        1         6\n",
-      "ulysses16     5      5    2        3        1         4\n",
-      "ulysses22     4      4    2        3        1         6\n",
-      "dantzig42     1      1    3        3        3         3\n",
+      "ulysses16     5      5    3        2        1         4\n",
+      "ulysses22     3      3    2        3        1         6\n",
       "att48         4      4    2        4        1         3\n",
+      "eil51         4      4    3        4        2         1\n",
       "...         ...    ...  ...      ...      ...       ...\n",
       "rl1304        5      5    3        4        1         2\n",
       "rl1323        3      3    6        2        1         5\n",
@@ -2799,15 +2803,15 @@
       "fl1400        4      4    2        6        1         3\n",
       "u1432         4      4    2        6        1         3\n",
       "\n",
-      "[74 rows x 6 columns]\n",
+      "[72 rows x 6 columns]\n",
       "\n",
       "各算法在所有实例上的平均排名:\n",
-      "贪心算法        3.77\n",
-      "最近邻算法       3.77\n",
-      "插入法         2.73\n",
-      "EoH-TSP     4.04\n",
-      "AAD-TSP     1.26\n",
-      "MEoH-TSP    3.24\n",
+      "贪心算法        3.82\n",
+      "最近邻算法       3.82\n",
+      "插入法         2.75\n",
+      "EoH-TSP     4.06\n",
+      "AAD-TSP     1.19\n",
+      "MEoH-TSP    3.25\n",
       "dtype: float64\n",
       "\n",
       "各算法在不同实例上的运行时长排名:\n",
@@ -2815,42 +2819,42 @@
       "burma14       2      1    3        5        6         4\n",
       "ulysses16     2      1    3        5        6         4\n",
       "ulysses22     1      2    3        5        6         4\n",
-      "dantzig42     1      1    3        3        3         3\n",
       "att48         2      1    4        5        6         3\n",
+      "eil51         2      1    4        5        6         3\n",
       "...         ...    ...  ...      ...      ...       ...\n",
-      "rl1304        2      1    6        4        5         3\n",
+      "rl1304        1      3    6        4        5         2\n",
       "rl1323        2      1    6        4        5         3\n",
-      "nrw1379       2      1    6        4        5         3\n",
-      "fl1400        2      1    5        4        6         3\n",
-      "u1432         3      2    6        4        5         1\n",
+      "nrw1379       1      2    6        4        5         3\n",
+      "fl1400        3      2    5        4        6         1\n",
+      "u1432         3      1    6        4        5         2\n",
       "\n",
-      "[74 rows x 6 columns]\n",
+      "[72 rows x 6 columns]\n",
       "\n",
       "各算法在所有实例上的平均运行时长排名:\n",
-      "贪心算法        1.61\n",
-      "最近邻算法       1.50\n",
-      "插入法         5.31\n",
-      "EoH-TSP     4.09\n",
+      "贪心算法        1.74\n",
+      "最近邻算法       1.43\n",
+      "插入法         5.44\n",
+      "EoH-TSP     4.12\n",
       "AAD-TSP     5.39\n",
-      "MEoH-TSP    2.92\n",
+      "MEoH-TSP    2.88\n",
       "dtype: float64\n",
       "\n",
       "各算法在所有实例上的平均路径长度:\n",
-      "贪心算法        389892.12\n",
-      "最近邻算法       389892.12\n",
-      "插入法               inf\n",
-      "EoH-TSP           inf\n",
-      "AAD-TSP           inf\n",
-      "MEoH-TSP          inf\n",
+      "贪心算法        400722.45\n",
+      "最近邻算法       400722.45\n",
+      "插入法         365681.25\n",
+      "EoH-TSP     400751.63\n",
+      "AAD-TSP     345580.06\n",
+      "MEoH-TSP    389168.81\n",
       "dtype: float64\n",
       "\n",
       "各算法在所有实例上的平均运行时长:\n",
-      "贪心算法        0.0184\n",
-      "最近邻算法       0.0182\n",
-      "插入法            inf\n",
-      "EoH-TSP        inf\n",
-      "AAD-TSP        inf\n",
-      "MEoH-TSP       inf\n",
+      "贪心算法         0.0213\n",
+      "最近邻算法        0.0215\n",
+      "插入法         23.1702\n",
+      "EoH-TSP      0.8359\n",
+      "AAD-TSP     13.9758\n",
+      "MEoH-TSP     0.0279\n",
       "dtype: float64\n"
      ]
     }
@@ -2887,7 +2891,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
@@ -3226,12 +3230,1793 @@
       "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
       "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
       "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
       "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "图片尺寸: 2316 x 1713 像素\n",
+      "图片尺寸: 2400 x 1800 像素\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.image.AxesImage at 0x141c1bd10>"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# 计算每个算法的平均路径长度和平均运行时间\n",
+    "avg_paths = df_results.mean()\n",
+    "avg_times = df_time.mean()\n",
+    "\n",
+    "# 创建散点图，设置更大的尺寸和DPI\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "\n",
+    "# 设置坐标轴范围\n",
+    "x_max = max(avg_times) * 2.8\n",
+    "y_max = max(avg_paths) * 1.05\n",
+    "x_min = -3\n",
+    "y_min = min(avg_paths) * 0.99\n",
+    "plt.xlim(x_min, x_max)\n",
+    "plt.ylim(y_min, y_max)\n",
+    "\n",
+    "# 定义不同算法的颜色和标记\n",
+    "colors = ['red', 'blue', 'green', 'purple', 'orange', 'brown', 'pink']\n",
+    "markers = ['o', 's', '^', 'D', 'v', '<', '>']\n",
+    "\n",
+    "# 算法名称映射\n",
+    "algo_names = {\n",
+    "    '贪心算法': 'Greedy',\n",
+    "    '最近邻算法': 'NN',\n",
+    "    '插入法': 'Insertion',\n",
+    "    'EoH-TSP': 'EoH',\n",
+    "    'AAD-TSP': 'AAE',\n",
+    "    'MEoH-TSP': 'MEoH'\n",
+    "}\n",
+    "\n",
+    "# 绘制散点和标注，增加点的大小和字体大小\n",
+    "for i, alg in enumerate(avg_paths.index):\n",
+    "    x = avg_times[alg]\n",
+    "    y = avg_paths[alg]\n",
+    "\n",
+    "    # 贪心算法的点的大小要比别的大1.5倍\n",
+    "    if alg == '贪心算法':\n",
+    "        plt.scatter(x, y,\n",
+    "                   color=colors[i % len(colors)],\n",
+    "                   marker=markers[i % len(markers)],\n",
+    "                   s=200,  # 增大点的大小\n",
+    "                   label=algo_names[alg])\n",
+    "    else:\n",
+    "        plt.scatter(x, y,\n",
+    "                    color=colors[i % len(colors)],\n",
+    "                    marker=markers[i % len(markers)],\n",
+    "                    s=100,  # 增大点的大小\n",
+    "                    label=algo_names[alg])\n",
+    "    \n",
+    "    if alg == 'EoH-TSP':\n",
+    "        xytext = (40, 30)\n",
+    "    else:\n",
+    "        xytext = (40, -5)\n",
+    "\n",
+    "    plt.annotate(f'({x:.2f}, {y:.2e})',\n",
+    "                xy=(x, y),\n",
+    "                xytext=xytext,\n",
+    "                textcoords='offset points',\n",
+    "                fontsize=18,  # 增大标注字体\n",
+    "                bbox=dict(facecolor='white', edgecolor='none', alpha=0.7))\n",
+    "\n",
+    "plt.xlabel('Average running time (seconds)', fontsize=18)\n",
+    "plt.ylabel('Average path length', fontsize=18)\n",
+    "\n",
+    "# 设置更大的刻度字体大小\n",
+    "plt.xticks(fontsize=14)\n",
+    "plt.yticks(fontsize=14)\n",
+    "\n",
+    "# 设置y轴为科学计数法显示\n",
+    "plt.ticklabel_format(style='sci', axis='y', scilimits=(0,0))\n",
+    "\n",
+    "# 添加更大的图例\n",
+    "plt.legend(fontsize=14, loc='upper right')\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.savefig('tsp_pareto.png', dpi=300, bbox_inches='tight')\n",
+    "plt.show()\n",
+    "\n",
+    "# 输出这张图片的精准大小\n",
+    "import os\n",
+    "import matplotlib.pyplot as plt\n",
+    "from PIL import Image\n",
+    "# 打开图片\n",
+    "image_path = 'tsp_pareto.png'\n",
+    "image = Image.open(image_path)\n",
+    "# 获取图片的尺寸\n",
+    "width, height = image.size\n",
+    "# 输出图片的尺寸\n",
+    "print(f\"图片尺寸: {width} x {height} 像素\")\n",
+    "# 对图片进行拉长拉宽强制到2400*1800像素 \n",
+    "image = image.resize((2400, 1800), Image.Resampling.LANCZOS)\n",
+    "# 保存图片\n",
+    "image.save(image_path)\n",
+    "# 输出图片的尺寸\n",
+    "image = Image.open(image_path)\n",
+    "width, height = image.size\n",
+    "print(f\"图片尺寸: {width} x {height} 像素\")\n",
+    "# 再次展示图片\n",
+    "plt.imshow(image)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Greedy: (0.02, 4.01e+05)\n",
+      "NN: (0.02, 4.01e+05)\n",
+      "Insertion: (23.17, 3.66e+05)\n",
+      "EoH: (0.84, 4.01e+05)\n",
+      "AAE: (13.98, 3.46e+05)\n",
+      "MEoH: (0.03, 3.89e+05)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 输出上面绘图中每个散点的名称以及两个分别的指标值\n",
+    "for i, alg in enumerate(avg_paths.index):\n",
+    "    x = avg_times[alg]\n",
+    "    y = avg_paths[alg]\n",
+    "    print(f\"{algo_names[alg]}: ({x:.2f}, {y:.2e})\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
+      "findfont: Generic family 'sans-serif' not found because none of the following families were found: SimHei\n",
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",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
diff --git a/tsp_data/tsp_time.png b/tsp_data/tsp_time.png
index 948052d..305fe4c 100644
Binary files a/tsp_data/tsp_time.png and b/tsp_data/tsp_time.png differ