{"id":3681,"date":"2022-07-20T09:00:00","date_gmt":"2022-07-20T00:00:00","guid":{"rendered":"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/?p=3681"},"modified":"2022-07-20T09:00:00","modified_gmt":"2022-07-20T00:00:00","slug":"%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0","status":"publish","type":"post","link":"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/","title":{"rendered":"\u81ea\u52d5\u8eca\u88fd\u9020\u306e\u5857\u88c5\u5de5\u7a0b\u3092\u5b9f\u969b\u306b\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3067\u6700\u9069\u5316\u3057\u3066\u307f\u305f"},"content":{"rendered":"\n<p><a href=\"https:\/\/colab.research.google.com\/github\/T-QARD\/t-wave\/blob\/main\/notebooks\/car_paint\/car_paint.ipynb\" target=\"_blank\" rel=\"noopener noreferrer\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" src=\"https:\/\/colab.research.google.com\/assets\/colab-badge.svg\" alt=\"Open in Colab\" width=\"117\" height=\"20\"><\/a><\/p>\n\n\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-white ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title ez-toc-toggle\" style=\"cursor:pointer\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E6%A6%82%E8%A6%81\" >\u6982\u8981<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E6%96%87%E7%8C%AE%E6%83%85%E5%A0%B1\" >\u6587\u732e\u60c5\u5831<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E5%95%8F%E9%A1%8C\" >\u554f\u984c<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E5%AE%9F%E9%A8%93\" >\u5b9f\u9a13<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E3%83%87%E3%83%BC%E3%82%BF%E3%82%BB%E3%83%83%E3%83%88%E3%81%AE%E4%BD%9C%E6%88%90\" >\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u4f5c\u6210<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E3%83%96%E3%83%A9%E3%83%83%E3%82%AF%E3%83%95%E3%82%A1%E3%83%BC%E3%82%B9%E3%83%88%E8%B2%AA%E6%AC%B2%E6%B3%95%E3%81%A7MCPS%E5%95%8F%E9%A1%8C%E3%82%92%E8%A7%A3%E3%81%8F\" >\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8(\u8caa\u6b32\u6cd5)\u3067MCPS\u554f\u984c\u3092\u89e3\u304f<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E3%82%B7%E3%83%9F%E3%83%A5%E3%83%AC%E3%83%BC%E3%83%86%E3%83%83%E3%83%89%E3%82%A2%E3%83%8B%E3%83%BC%E3%83%AA%E3%83%B3%E3%82%B0%E3%81%AE%E5%88%A9%E7%94%A8\" >\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u5229\u7528<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E5%95%8F%E9%A1%8C%E3%82%92%E8%A7%A3%E3%81%84%E3%81%9F%E7%AD%94%E3%81%88%E3%82%92%E8%A9%95%E4%BE%A1%E3%81%99%E3%82%8B%E9%96%A2%E6%95%B0%E3%81%AE%E5%AE%9A%E7%BE%A9\" >\u554f\u984c\u3092\u89e3\u3044\u305f\u7b54\u3048\u3092\u8a55\u4fa1\u3059\u308b\u95a2\u6570\u306e\u5b9a\u7fa9<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E6%AF%94%E8%BC%83%E5%AE%9F%E9%A8%93\" >\u6bd4\u8f03\u5b9f\u9a13<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E7%B5%90%E8%AB%96\" >\u7d50\u8ad6<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E3%81%82%E3%81%A8%E3%81%8C%E3%81%8D\" >\u3042\u3068\u304c\u304d<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/qard.is.tohoku.ac.jp\/T-Wave\/2022\/07\/20\/%e8%87%aa%e5%8b%95%e8%bb%8a%e8%a3%bd%e9%80%a0%e3%81%ae%e5%a1%97%e8%a3%85%e5%b7%a5%e7%a8%8b%e3%82%92%e5%ae%9f%e9%9a%9b%e3%81%ab%e9%87%8f%e5%ad%90%e3%82%a2%e3%83%8b%e3%83%bc%e3%83%aa%e3%83%b3%e3%82%b0\/#%E6%8B%85%E5%BD%93%E8%80%85\" >\u62c5\u5f53\u8005<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"%E6%A6%82%E8%A6%81\"><\/span>\u6982\u8981<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u8a18\u4e8b\u300c<a href=\"\/T-Wave\/?p=3209\">\u81ea\u52d5\u8eca\u88fd\u9020\u306e\u5857\u88c5\u5de5\u7a0b\u3092\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3067\u6700\u9069\u5316\u3059\u308b<\/a>\u300d\u3067\u306f\u3001\u30de\u30eb\u30c1\u30ab\u30fc\u30da\u30a4\u30f3\u30c8\u30b7\u30e7\u30c3\u30d7\u554f\u984c\u3092\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u3084\u53e4\u5178\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u306a\u3069\u306e\u3055\u307e\u3056\u307e\u306a\u65b9\u6cd5\u3067\u89e3\u304d\u3001\u305d\u306e\u6027\u80fd\u306b\u5bfe\u3059\u308b\u6bd4\u8f03\u3092\u884c\u306a\u3063\u305f\u8ad6\u6587\u3092\u7d39\u4ecb\u3057\u305f\u3002<br>\u672c\u8a18\u4e8b\u3067\u306f\u3001\u8ad6\u6587\u5185\u306b\u767b\u5834\u3057\u305f\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u3068\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u5b9f\u88c5\u5b9f\u9a13\u3092\u884c\u3044\u3001\u7d50\u679c\u3092\u6bd4\u8f03\u3057\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E6%96%87%E7%8C%AE%E6%83%85%E5%A0%B1\"><\/span>\u6587\u732e\u60c5\u5831<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<ul style=\"list-style-type: disc;\">\n<li>\u30bf\u30a4\u30c8\u30eb\uff1aMulti-car paint shop optimization with quantum annealing<\/li>\n<li>\u8457\u8005\uff1aSheir Yarkoni, Alex Alekseyenko, Michael Streif, David Von Dollen, Florian Neukart, Thomas B\u00e4ck<\/li>\n<li>\u66f8\u8a8c\u60c5\u5831\uff1a<a href=\"https:\/\/arxiv.org\/abs\/2109.07876\">arXiv:2109.07876<\/a><\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E5%95%8F%E9%A1%8C\"><\/span>\u554f\u984c<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u30de\u30eb\u30c1\u30ab\u30fc\u30da\u30a4\u30f3\u30c8\u30b7\u30e7\u30c3\u30d7\u554f\u984c\u306f\u3001\u30de\u30eb\u30c1\u30ab\u30fc\u30da\u30a4\u30f3\u30c8\u30b7\u30e7\u30c3\u30d7\u554f\u984c\u3068\u306f\u3001\u300c\u8eca\u306b\u5857\u308b\u5857\u6599\u306e\u8272\u306e\u5909\u66f4\u56de\u6570\u3092\u3044\u304b\u306b\u5c11\u306a\u304f\u3059\u308b\u304b\u300d\u3068\u3044\u3046\u6700\u9069\u5316\u554f\u984c\u3067\u3042\u308b\u3002\u8a73\u7d30\u306a\u5185\u5bb9\u306f<a href=\"\/T-Wave\/?p=3209\">\u300c\u81ea\u52d5\u8eca\u88fd\u9020\u306e\u5857\u88c5\u5de5\u7a0b\u3092\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3067\u6700\u9069\u5316\u3059\u308b\u300d<\/a>\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E5%AE%9F%E9%A8%93\"><\/span>\u5b9f\u9a13<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u307e\u305a\u3001\u554f\u984c\u3092\u89e3\u304f\u305f\u3081\u306b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f5c\u308a\u3001\u554f\u984c\u3092\u89e3\u304f\u305f\u3081\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u4e8c\u3064\u7528\u610f\u3059\u308b\u3002\u4e00\u3064\u76ee\u306f\u3001\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u3001\u4e8c\u3064\u76ee\u306f\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3067\u3042\u308b\u3002\u305d\u308c\u305e\u308c\u306e\u7279\u5fb4\u306f\u95a2\u6570\u306e\u5b9a\u7fa9\u3067\u8aac\u660e\u3059\u308b\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h3><span class=\"ez-toc-section\" id=\"%E3%83%87%E3%83%BC%E3%82%BF%E3%82%BB%E3%83%83%E3%83%88%E3%81%AE%E4%BD%9C%E6%88%90\"><\/span>\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u4f5c\u6210<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u307e\u305a\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f5c\u6210\u3059\u308b\u95a2\u6570\u306e\u4f5c\u6210\u3092\u884c\u3063\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"c1\"># \u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">pandas<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">pd<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">numpy<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">np<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">random<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">matplotlib<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">mpl<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">pandas<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">pd<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">seaborn<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">sns<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"sd\">\"\"\"<\/span>\n<span class=\"sd\">mkdata\u95a2\u6570\u3092\u4f7f\u3063\u3066\u5f97\u3089\u308c\u308b\u30c7\u30fc\u30bf\u306f\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u308b.<\/span>\n<span class=\"sd\">\u30fbdata_1:\u8eca\u306e\u5f85\u3061\u884c\u5217\u306e\u30ea\u30b9\u30c8\u578b\u30c7\u30fc\u30bf<\/span>\n<span class=\"sd\">\u30fbNofC:\u3042\u308b\u8eca\u7a2ei\u3068\u3044\u3046\u8eca\u306e\u53f0\u6570\u3092\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u3054\u3068\u306b\u8a18\u9332\u3059\u308b\u30ea\u30b9\u30c8\u578b\u30c7\u30fc\u30bf<\/span>\n<span class=\"sd\">\u30fbkC:\u3042\u308b\u8eca\u7a2ei\u3068\u3044\u3046\u8eca\u3092\u9ed2\u306b\u5857\u308b\u53f0\u6570\u3092\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u3054\u3068\u306b\u8a18\u9332\u3059\u308b\u30ea\u30b9\u30c8\u578b\u30c7\u30fc\u30bf<\/span>\n<span class=\"sd\">\u30fbAC:\u3042\u308b\u8eca\u7a2ei\u3068\u3044\u3046\u8eca\u306fdata_1\u306e\u3069\u306e\u4f4d\u7f6e\u306b\u3044\u308b\u306e\u304b\u3092\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u3054\u3068\u306b\u8a18\u9332\u3057\u305f\u30ea\u30b9\u30c8\u578b\u30c7\u30fc\u30bf<\/span>\n\n<span class=\"sd\">\u3053\u308c\u3089\u3092\u4f5c\u6210\u3059\u308bmkdata\u95a2\u6570\u3092\u4f5c\u6210\u3059\u308b.<\/span>\n<span class=\"sd\">\u5f15\u6570\u306fN(\u554f\u984c\u30b5\u30a4\u30ba), carkind(\u554f\u984c\u3067\u6700\u9069\u5316\u3059\u308b\u8eca\u306e\u7a2e\u985e)<\/span>\n<span class=\"sd\">\u8fd4\u308a\u5024\u306fdata_1, NofC, kC, AC\u3067\u3042\u308b\u3002<\/span>\n<span class=\"sd\">\"\"\"<\/span>\n\n\n<span class=\"k\">def<\/span> <span class=\"nf\">mkdata<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">carkind<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># \u30c7\u30fc\u30bf\u306e\u751f\u6210<\/span>\n    <span class=\"n\">data_1<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>  <span class=\"c1\"># \u3069\u306e\u8eca\u7a2e\u304c\u3069\u306e\u9806\u756a\u3067\u4e26\u3093\u3067\u3044\u308b\u304b\u3092\u793a\u3059\u914d\u5217<\/span>\n    <span class=\"n\">kC<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>  <span class=\"c1\"># \u8eca\u7a2e\u3054\u3068\u306b\u9ed2\u304f\u5857\u308b\u53f0\u6570\u3092\u4f55\u53f0\u306b\u3059\u308b\u304b\u3092\u633f\u5165\u3059\u308b\u914d\u5217<\/span>\n    <span class=\"n\">NofC<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>  <span class=\"c1\"># \u8eca\u7a2e\u3054\u3068\u306e\u8981\u7d20\u6570\u3092\u6c7a\u3081\u308b\u914d\u5217<\/span>\n    <span class=\"n\">AC<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>  <span class=\"c1\"># \u3042\u308b\u8eca\u7a2e\u304c\u3069\u306e\u4f4d\u7f6e\u306b\u4e26\u3093\u3067\u3044\u308b\u304b\u3092\u30ea\u30b9\u30c8\u5f62\u5f0f\u3067\u8a18\u61b6\u3059\u308b\u914d\u5217<\/span>\n\n    <span class=\"c1\"># \u30c7\u30fc\u30bf\u306e\u683c\u7d0d1(\u8eca\u306e\u7a2e\u985e\u3068\u9806\u756a\u3092\u3092\u30e9\u30f3\u30c0\u30e0\u306b\u6c7a\u3081\u308b)<\/span>\n    <span class=\"k\">while<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">data_1<\/span><span class=\"p\">)<\/span> <span class=\"o\">!=<\/span> <span class=\"n\">N<\/span><span class=\"p\">:<\/span>\n        <span class=\"k\">if<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">data_1<\/span><span class=\"p\">)<\/span> <span class=\"o\">&lt;=<\/span> <span class=\"mf\">0.7<\/span> <span class=\"o\">*<\/span> <span class=\"n\">N<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">new_value<\/span> <span class=\"o\">=<\/span> <span class=\"n\">random<\/span><span class=\"o\">.<\/span><span class=\"n\">randint<\/span><span class=\"p\">(<\/span><span class=\"mi\">0<\/span><span class=\"p\">,<\/span> <span class=\"p\">(<\/span><span class=\"n\">carkind<\/span> <span class=\"o\">-<\/span> <span class=\"mi\">1<\/span><span class=\"p\">))<\/span>\n            <span class=\"c1\"># \u540c\u3058\u8eca\u7a2e\u30922\u56de\u53d6\u308a\u8fbc\u3080<\/span>\n            <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"mi\">2<\/span><span class=\"p\">):<\/span>\n                <span class=\"n\">data_1<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">new_value<\/span><span class=\"p\">)<\/span>\n        <span class=\"k\">else<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">data_1<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">random<\/span><span class=\"o\">.<\/span><span class=\"n\">randint<\/span><span class=\"p\">(<\/span><span class=\"mi\">0<\/span><span class=\"p\">,<\/span> <span class=\"p\">(<\/span><span class=\"n\">carkind<\/span> <span class=\"o\">-<\/span> <span class=\"mi\">1<\/span><span class=\"p\">)))<\/span>\n    <span class=\"n\">random<\/span><span class=\"o\">.<\/span><span class=\"n\">shuffle<\/span><span class=\"p\">(<\/span><span class=\"n\">data_1<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"c1\"># \u30c7\u30fc\u30bf\u306e\u683c\u7d0d2(\u9ed2\u306b\u5857\u308b\u8eca\u306e\u6570\u3092\u8eca\u306e\u7a2e\u985e\u9806\u306b\u5224\u65ad)<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">carkind<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">nCar<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>  <span class=\"c1\"># \u8eca\u7a2e\u3054\u3068\u306e\u8981\u7d20\u6570\u3092\u683c\u7d0d\u3059\u308b\u5909\u6570<\/span>\n        <span class=\"n\">nCar<\/span> <span class=\"o\">=<\/span> <span class=\"n\">data_1<\/span><span class=\"o\">.<\/span><span class=\"n\">count<\/span><span class=\"p\">(<\/span><span class=\"n\">i<\/span><span class=\"p\">)<\/span>  <span class=\"c1\"># i\u3068\u3044\u3046\u8eca\u7a2e\u304c\u4f55\u53f0\u3042\u308b\u304b\u3092\u63a2\u7d22\u3059\u308b<\/span>\n        <span class=\"n\">kC<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">random<\/span><span class=\"o\">.<\/span><span class=\"n\">randint<\/span><span class=\"p\">(<\/span><span class=\"mi\">0<\/span><span class=\"p\">,<\/span> <span class=\"n\">nCar<\/span><span class=\"p\">))<\/span>  <span class=\"c1\"># 0~nCar\u306e\u53f0\u6570\u306e\u3046\u3061\u9ed2\u306b\u5857\u308b\u53f0\u6570\u3092\u6c7a\u3081\u308b<\/span>\n\n    <span class=\"c1\"># \u30c7\u30fc\u30bf\u306e\u683c\u7d0d3(\u3042\u308b\u8eca\u7a2e\u304c\u3069\u306e\u4f4d\u7f6e\u306b\u4e26\u3093\u3067\u3044\u308b\u304b\u3092\u308f\u304b\u308b\u3088\u3046\u306b\u3059\u308b)<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">carkind<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">AC<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">([<\/span><span class=\"n\">n<\/span> <span class=\"k\">for<\/span> <span class=\"n\">n<\/span><span class=\"p\">,<\/span> <span class=\"n\">v<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">enumerate<\/span><span class=\"p\">(<\/span><span class=\"n\">data_1<\/span><span class=\"p\">)<\/span> <span class=\"k\">if<\/span> <span class=\"n\">v<\/span> <span class=\"o\">==<\/span> <span class=\"n\">i<\/span><span class=\"p\">])<\/span>\n\n    <span class=\"n\">count<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>  <span class=\"c1\"># \u56fa\u5b9a\u3055\u308c\u308b\u8eca\u4e21\u3092\u30ab\u30a6\u30f3\u30c8\u3059\u308b\u5909\u6570<\/span>\n\n    <span class=\"c1\"># \u56fa\u5b9a\u3055\u308c\u308b\u8eca\u4e21\u3092\u30ab\u30a6\u30f3\u30c8\u3059\u308b<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">carkind<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">nCar<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>  <span class=\"c1\"># \u8eca\u7a2e\u3054\u3068\u306e\u8981\u7d20\u6570\u3092\u683c\u7d0d\u3059\u308b\u5909\u6570<\/span>\n        <span class=\"n\">nCar<\/span> <span class=\"o\">=<\/span> <span class=\"n\">data_1<\/span><span class=\"o\">.<\/span><span class=\"n\">count<\/span><span class=\"p\">(<\/span><span class=\"n\">i<\/span><span class=\"p\">)<\/span>  <span class=\"c1\"># i\u3068\u3044\u3046\u8eca\u7a2e\u304c\u4f55\u53f0\u3042\u308b\u304b\u3092\u63a2\u7d22\u3059\u308b<\/span>\n        <span class=\"n\">NofC<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">nCar<\/span><span class=\"p\">)<\/span>  <span class=\"c1\"># NofC\u914d\u5217\u306bi\u3068\u3044\u3046\u8eca\u7a2e\u306f\u4f55\u53f0\u3042\u308b\u306e\u304b\u3092\u8a18\u61b6\u3055\u305b\u308b<\/span>\n        <span class=\"k\">if<\/span> <span class=\"p\">(<\/span><span class=\"n\">kC<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">==<\/span> <span class=\"mi\">0<\/span><span class=\"p\">)<\/span> <span class=\"ow\">or<\/span> <span class=\"p\">(<\/span><span class=\"n\">kC<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">==<\/span> <span class=\"n\">nCar<\/span><span class=\"p\">):<\/span>\n            <span class=\"n\">count<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">nCar<\/span>\n\n    <span class=\"k\">return<\/span> <span class=\"n\">data_1<\/span><span class=\"p\">,<\/span> <span class=\"n\">NofC<\/span><span class=\"p\">,<\/span> <span class=\"n\">kC<\/span><span class=\"p\">,<\/span> <span class=\"n\">AC<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f5c\u308b\u95a2\u6570\u304c\u3067\u304d\u305f\u306e\u3067\u3001\u6b21\u306f\u5404\u7a2e\u30bd\u30eb\u30d0\u30fc(\u554f\u984c\u3092\u89e3\u304f\u30d7\u30ed\u30b0\u30e9\u30e0)\u3092\u7528\u3044\u3066\u554f\u984c\u3092\u89e3\u3044\u3066\u3044\u304f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h3><span class=\"ez-toc-section\" id=\"%E3%83%96%E3%83%A9%E3%83%83%E3%82%AF%E3%83%95%E3%82%A1%E3%83%BC%E3%82%B9%E3%83%88%E8%B2%AA%E6%AC%B2%E6%B3%95%E3%81%A7MCPS%E5%95%8F%E9%A1%8C%E3%82%92%E8%A7%A3%E3%81%8F\"><\/span>\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8(\u8caa\u6b32\u6cd5)\u3067MCPS\u554f\u984c\u3092\u89e3\u304f<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u306f\u3058\u3081\u306b\u3001\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u3068\u547c\u3070\u308c\u308b\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3067MPCS\u554f\u984c\u3092\u89e3\u3044\u3066\u3044\u304f\u3053\u3068\u306b\u3059\u308b.<\/p>\n<p>\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306f\u3001\u30de\u30eb\u30c1\u30ab\u30fc\u30da\u30a4\u30f3\u30c8\u30b7\u30e7\u30c3\u30d7\u554f\u984c\u3092\u89e3\u304f\u305f\u3081\u306b\u8caa\u6b32\u306b\u63a2\u7d22\u3059\u308b\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3067\u3042\u308b\u3002\u65b9\u6cd5\u3068\u3057\u3066\u306f\u3001\u3042\u308b\u8eca\u7a2e[latex]C_l[\/latex]([latex]l\\in 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\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\" alt=\"\u30da\u30a4\u30f3\u30c8\u30b7\u30e7\u30c3\u30d7\u554f\u984c4.jpg\"><\/p>\n<p>\u56f31\uff1a\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306e\u30a4\u30e1\u30fc\u30b8<\/p>\n<p>\u307e\u305a, \u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u3067\u554f\u984c\u3092\u51e6\u7406\u3059\u308bblackfirst\u95a2\u6570\u3092\u5b9a\u7fa9\u3059\u308b\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"sd\">\"\"\"<\/span>\n<span class=\"sd\">\u5f15\u6570\u306fN, carkind, data_1, kC<\/span>\n<span class=\"sd\">\u8fd4\u308a\u5024\u306fbf_solution(\u5f85\u3061\u884c\u5217\u9806\u306b\u3001\u8eca\u306b\u9ed2(1)\u304b\u767d(-1)\u3069\u3061\u3089\u306e\u8272\u3092\u5857\u308c\u3070\u826f\u3044\u306e\u304b\u3092\u6c7a\u3081\u308b\u30ea\u30b9\u30c8)\u3067\u3042\u308b\u3002<\/span>\n<span class=\"sd\">\"\"\"<\/span>\n\n\n<span class=\"k\">def<\/span> <span class=\"nf\">blackfirst<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">carkind<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_1<\/span><span class=\"p\">,<\/span> <span class=\"n\">kC<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># \u89e3\u306e\u5b9a\u7fa9<\/span>\n    <span class=\"n\">bf_solution<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"c1\"># kC\u306e\u30b3\u30d4\u30fc\u3092\u4f5c\u308b<\/span>\n    <span class=\"n\">kC_copy<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">carkind<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">kC_copy<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">kC<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">])<\/span>\n    <span class=\"c1\"># data_1\u3092\u524d\u304b\u3089\u9806\u756a\u306b\u898b\u3066\u3044\u304d\u3001\u8eca\u7a2e\u306e\u756a\u53f7\u306b\u9ed2\u3092\u5857\u3063\u3066\u3082\u3044\u3044\u306a\u3089\u307e\u305a\u9ed2\u3092\u5857\u308b\u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u4f5c\u6210\u3059\u308b\u3002<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">):<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">kC_copy<\/span><span class=\"p\">[<\/span><span class=\"n\">data_1<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]]<\/span> <span class=\"o\">&gt;<\/span> <span class=\"mi\">0<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">bf_solution<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"mi\">1<\/span><span class=\"p\">)<\/span>\n            <span class=\"n\">kC_copy<\/span><span class=\"p\">[<\/span><span class=\"n\">data_1<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]]<\/span> <span class=\"o\">-=<\/span> <span class=\"mi\">1<\/span>\n        <span class=\"k\">else<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">bf_solution<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"o\">-<\/span><span class=\"mi\">1<\/span><span class=\"p\">)<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">bf_solution<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h3><span class=\"ez-toc-section\" id=\"%E3%82%B7%E3%83%9F%E3%83%A5%E3%83%AC%E3%83%BC%E3%83%86%E3%83%83%E3%83%89%E3%82%A2%E3%83%8B%E3%83%BC%E3%83%AA%E3%83%B3%E3%82%B0%E3%81%AE%E5%88%A9%E7%94%A8\"><\/span>\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u5229\u7528<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u6b21\u306b\u3001\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3092\u4f7f\u3063\u3066\u554f\u984c\u3092\u89e3\u304b\u305b\u308b\u3002<br>\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3068\u306f\u3001\u91d1\u5c5e\u306e\u6e29\u5ea6\u3092\u4e0a\u3052\u3001\u51b7\u307e\u3057\u3066\u3044\u304f\u904e\u7a0b\u3067\u79e9\u5e8f\u306e\u3042\u308b\u69cb\u9020\u3092\u4f5c\u308a\u51fa\u3059\u69d8\u5b50\u3092\u53e4\u5178\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u3067\u518d\u73fe\u3057\u305f\u3082\u306e\u3067\u3042\u308b\u3002\u3053\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u4f7f\u3063\u3066\u554f\u984c\u306e\u6700\u9069\u89e3\u306e\u63a2\u7d22\u3092\u884c\u3044\u3001\u305d\u308c\u306b\u3088\u3063\u3066\u6700\u9069\u5316\u554f\u984c\u3092\u89e3\u304f\u3002<\/p>\n<p>\u4eca\u56de\u306fpyqubo\u3068dimod\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u3063\u3066\u89e3\u304f\u3053\u3068\u306b\u3057\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"c1\"># openjij\u3068pyqubo\u306e\u30a4\u30f3\u30dd\u30fc\u30c8<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">dimod<\/span>\n<span class=\"kn\">from<\/span> <span class=\"nn\">pyqubo<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">Array<\/span><span class=\"p\">,<\/span> <span class=\"n\">Constraint<\/span><span class=\"p\">,<\/span> <span class=\"n\">solve_qubo<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u4eca\u56de\u306e\u554f\u984c\u306e\u30a4\u30b8\u30f3\u30b0\u30e2\u30c7\u30eb\u306e\u30cf\u30df\u30eb\u30c8\u30cb\u30a2\u30f3\u306f\u6b21\u306e\u3088\u3046\u306b\u5b9a\u7fa9\u3055\u308c\u308b\u3002<br>\\begin{equation*}<br>H_A :=\\,- \\sum^{N-2}_{i=0} s_i s_{i+1}\\\\<br>H_B :=\\sum_{C_l\\in C}\\{(\\#C_l-2k(C_l))\\sum_{j\\in A(C_l)}s_j + \\sum_{i&lt;j \\in A(C_l)}s_i s_j\\}\\\\<br>H_{MCPS} = H_A+\\lambda H_B<br>\\end{equation*}<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u3053\u3053\u3067\u3001[latex]H_B[\/latex]\u306e[latex]\\{\\}[\/latex]\u5185\u306e\u7b2c\u4e8c\u9805\u306e[latex]\\sum_{i&lt;j\\in A(C_l)}s_is_j[\/latex]\u3092\u8a08\u7b97\u3059\u308b\u305f\u3081\u306esumij\u95a2\u6570\u3092\u5b9a\u7fa9\u3059\u308b\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"c1\"># \u30cf\u30df\u30eb\u30c8\u30cb\u30a2\u30f3H_B\u5185\u3067\u4f7f\u3046sumij\u95a2\u6570\u3092\u5b9a\u7fa9\u3059\u308b<\/span>\n<span class=\"k\">def<\/span> <span class=\"nf\">sumij<\/span><span class=\"p\">(<\/span><span class=\"n\">lisA<\/span><span class=\"p\">,<\/span> <span class=\"n\">s<\/span><span class=\"p\">):<\/span>\n    <span class=\"nb\">sum<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">lisA<\/span><span class=\"p\">)<\/span> <span class=\"o\">-<\/span> <span class=\"mi\">1<\/span><span class=\"p\">):<\/span>\n        <span class=\"k\">for<\/span> <span class=\"n\">j<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">i<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">,<\/span> <span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">lisA<\/span><span class=\"p\">)):<\/span>\n            <span class=\"nb\">sum<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">s<\/span><span class=\"p\">[<\/span><span class=\"n\">lisA<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">s<\/span><span class=\"p\">[<\/span><span class=\"n\">lisA<\/span><span class=\"p\">[<\/span><span class=\"n\">j<\/span><span class=\"p\">]]<\/span>\n    <span class=\"k\">return<\/span> <span class=\"nb\">sum<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"sd\">\"\"\"<\/span>\n<span class=\"sd\">SA\u3067MCPS\u554f\u984c\u3092\u89e3\u304fsimulatedannealing\u95a2\u6570\u3092\u5b9a\u7fa9\u3059\u308b\u3002<\/span>\n<span class=\"sd\">\u5f15\u6570\u306fdata_1, NofC, kC, AC<\/span>\n<span class=\"sd\">\u8fd4\u308a\u5024\u306fsa_solution\u3067\u3042\u308b\u3002<\/span>\n<span class=\"sd\">\"\"\"<\/span>\n\n\n<span class=\"k\">def<\/span> <span class=\"nf\">simulatedannealing<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">carkind<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_1<\/span><span class=\"p\">,<\/span> <span class=\"n\">NofC<\/span><span class=\"p\">,<\/span> <span class=\"n\">kC<\/span><span class=\"p\">,<\/span> <span class=\"n\">AC<\/span><span class=\"p\">):<\/span>\n    <span class=\"c1\"># 1\u6b21\u5143\u306e\u914d\u5217\u3092\u5b9a\u7fa9\u3059\u308b\u3002<\/span>\n    <span class=\"n\">s<\/span> <span class=\"o\">=<\/span> <span class=\"n\">Array<\/span><span class=\"o\">.<\/span><span class=\"n\">create<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"s\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">shape<\/span><span class=\"o\">=<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">),<\/span> <span class=\"n\">vartype<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"SPIN\"<\/span><span class=\"p\">)<\/span>\n    <span class=\"c1\"># \u30cf\u30df\u30eb\u30c8\u30cb\u30a2\u30f3\u306e\u5b9a\u7fa9<\/span>\n    <span class=\"n\">H_A<\/span> <span class=\"o\">=<\/span> <span class=\"o\">-<\/span><span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">s<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">s<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">s<\/span><span class=\"p\">)<\/span> <span class=\"o\">-<\/span> <span class=\"mi\">2<\/span><span class=\"p\">))<\/span>\n    <span class=\"n\">H_B<\/span> <span class=\"o\">=<\/span> <span class=\"n\">Constraint<\/span><span class=\"p\">(<\/span>\n        <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span>\n            <span class=\"p\">(<\/span><span class=\"n\">NofC<\/span><span class=\"p\">[<\/span><span class=\"n\">l<\/span><span class=\"p\">]<\/span> <span class=\"o\">-<\/span> <span class=\"mi\">2<\/span> <span class=\"o\">*<\/span> <span class=\"n\">kC<\/span><span class=\"p\">[<\/span><span class=\"n\">l<\/span><span class=\"p\">])<\/span> <span class=\"o\">*<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">s<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">AC<\/span><span class=\"p\">[<\/span><span class=\"n\">l<\/span><span class=\"p\">])<\/span> <span class=\"o\">+<\/span> <span class=\"n\">sumij<\/span><span class=\"p\">(<\/span><span class=\"n\">AC<\/span><span class=\"p\">[<\/span><span class=\"n\">l<\/span><span class=\"p\">],<\/span> <span class=\"n\">s<\/span><span class=\"p\">)<\/span>\n            <span class=\"k\">for<\/span> <span class=\"n\">l<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">carkind<\/span><span class=\"p\">)<\/span>\n        <span class=\"p\">),<\/span>\n        <span class=\"n\">label<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"H_B\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"p\">)<\/span>\n    <span class=\"n\">Q<\/span> <span class=\"o\">=<\/span> <span class=\"n\">H_A<\/span> <span class=\"o\">+<\/span> <span class=\"n\">N<\/span> <span class=\"o\">*<\/span> <span class=\"n\">H_B<\/span>\n    <span class=\"c1\"># \u30e2\u30c7\u30eb\u306e\u30b3\u30f3\u30d1\u30a4\u30eb<\/span>\n    <span class=\"n\">model<\/span> <span class=\"o\">=<\/span> <span class=\"n\">Q<\/span><span class=\"o\">.<\/span><span class=\"n\">compile<\/span><span class=\"p\">()<\/span>\n    <span class=\"n\">ising<\/span><span class=\"p\">,<\/span> <span class=\"n\">offset<\/span><span class=\"p\">,<\/span> <span class=\"n\">fl<\/span> <span class=\"o\">=<\/span> <span class=\"n\">model<\/span><span class=\"o\">.<\/span><span class=\"n\">to_ising<\/span><span class=\"p\">(<\/span><span class=\"n\">index_label<\/span><span class=\"o\">=<\/span><span class=\"kc\">True<\/span><span class=\"p\">)<\/span>\n    <span class=\"c1\"># dimod\u306eSA\u3092\u7528\u3044\u3066\u89e3\u304f\u3002<\/span>\n    <span class=\"n\">num_reads<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">10<\/span>\n    <span class=\"n\">sampler<\/span> <span class=\"o\">=<\/span> <span class=\"n\">dimod<\/span><span class=\"o\">.<\/span><span class=\"n\">SimulatedAnnealingSampler<\/span><span class=\"p\">()<\/span>\n    <span class=\"n\">response<\/span> <span class=\"o\">=<\/span> <span class=\"n\">sampler<\/span><span class=\"o\">.<\/span><span class=\"n\">sample_ising<\/span><span class=\"p\">(<\/span><span class=\"n\">ising<\/span><span class=\"p\">,<\/span> <span class=\"n\">offset<\/span><span class=\"p\">)<\/span>\n\n    <span class=\"c1\"># \u30a8\u30cd\u30eb\u30ae\u30fc\u304c\u4e00\u756a\u5c0f\u3055\u3044\u89e3(\u6700\u9069\u89e3\u306b\u8fd1\u3044\u89e3)\u3092\u9078\u3076\u3002<\/span>\n    <span class=\"n\">ene<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"n\">ene<\/span> <span class=\"o\">=<\/span> <span class=\"n\">response<\/span><span class=\"o\">.<\/span><span class=\"n\">data_vectors<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"energy\"<\/span><span class=\"p\">]<\/span>\n    <span class=\"n\">ene_min<\/span> <span class=\"o\">=<\/span> <span class=\"mf\">0.0<\/span>\n    <span class=\"n\">ene_min<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">min<\/span><span class=\"p\">(<\/span><span class=\"n\">ene<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">est<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"n\">est<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">where<\/span><span class=\"p\">(<\/span><span class=\"n\">ene<\/span> <span class=\"o\">==<\/span> <span class=\"n\">ene_min<\/span><span class=\"p\">)[<\/span><span class=\"mi\">0<\/span><span class=\"p\">][<\/span><span class=\"mi\">0<\/span><span class=\"p\">]<\/span>\n\n    <span class=\"c1\"># \u5f97\u3089\u308c\u305f\u7d50\u679c\u3092\u30c7\u30b3\u30fc\u30c9\u3059\u308b\u3002<\/span>\n    <span class=\"n\">decoded_sample<\/span> <span class=\"o\">=<\/span> <span class=\"n\">model<\/span><span class=\"o\">.<\/span><span class=\"n\">decode_sample<\/span><span class=\"p\">(<\/span><span class=\"n\">response<\/span><span class=\"o\">.<\/span><span class=\"n\">record<\/span><span class=\"p\">[<\/span><span class=\"n\">est<\/span><span class=\"p\">][<\/span><span class=\"mi\">0<\/span><span class=\"p\">],<\/span> <span class=\"n\">vartype<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"SPIN\"<\/span><span class=\"p\">)<\/span>\n    <span class=\"c1\"># \u3055\u3089\u306b\u89e3\u3092\u898b\u3084\u3059\u304f\u3059\u308b\u51e6\u7406\u3092\u8ffd\u52a0\u3059\u308b\u3002<\/span>\n    <span class=\"n\">sa_solution<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">):<\/span>\n        <span class=\"n\">sa_solution<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">decoded_sample<\/span><span class=\"o\">.<\/span><span class=\"n\">array<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"s\"<\/span><span class=\"p\">,<\/span> <span class=\"p\">(<\/span><span class=\"n\">i<\/span><span class=\"p\">)))<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">sa_solution<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E5%95%8F%E9%A1%8C%E3%82%92%E8%A7%A3%E3%81%84%E3%81%9F%E7%AD%94%E3%81%88%E3%82%92%E8%A9%95%E4%BE%A1%E3%81%99%E3%82%8B%E9%96%A2%E6%95%B0%E3%81%AE%E5%AE%9A%E7%BE%A9\"><\/span>\u554f\u984c\u3092\u89e3\u3044\u305f\u7b54\u3048\u3092\u8a55\u4fa1\u3059\u308b\u95a2\u6570\u306e\u5b9a\u7fa9<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u3068\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3067\u554f\u984c\u3092\u89e3\u3044\u305f\u5f8c\u3001\u305d\u306e\u89e3\u304c\u5236\u7d04\u3092\u6e80\u305f\u3057\u3066\u3044\u308b\u304b\u3069\u3046\u304b\u3068\u3001\u8272\u306e\u5207\u308a\u66ff\u3048\u56de\u6570\u304c\u4f55\u56de\u304b\u3092\u8a08\u7b97\u3059\u308b\u95a2\u6570\u3092\u5b9a\u7fa9\u3057\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"sd\">\"\"\"<\/span>\n<span class=\"sd\">\u7b54\u3048\u304c\u3069\u308c\u3060\u3051\u9055\u53cd\u3057\u3066\u3044\u308b\u304b\u306e\u5224\u5b9a\u3092\u3059\u308b\u95a2\u6570<\/span>\n<span class=\"sd\">\u5f15\u6570\u306fN, carkind, solution(MCPS\u554f\u984c\u3092\u89e3\u3044\u305f\u7b54\u3048), kC<\/span>\n<span class=\"sd\">\u8fd4\u308a\u5024\u306finvalid_rate(\u7b54\u3048\u304c\u5236\u7d04\u3092\u9055\u53cd\u3057\u3066\u3044\u308b\u5272\u5408\u3092%\u3067\u8fd4\u3059.)<\/span>\n<span class=\"sd\">\"\"\"<\/span>\n<span class=\"kn\">from<\/span> <span class=\"nn\">decimal<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">Decimal<\/span><span class=\"p\">,<\/span> <span class=\"n\">ROUND_HALF_UP<\/span><span class=\"p\">,<\/span> <span class=\"n\">ROUND_HALF_EVEN<\/span>\n\n\n<span class=\"k\">def<\/span> <span class=\"nf\">judge_ans<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">carkind<\/span><span class=\"p\">,<\/span> <span class=\"n\">solution<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_1<\/span><span class=\"p\">,<\/span> <span class=\"n\">kC<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">jud<\/span> <span class=\"o\">=<\/span> <span class=\"n\">np<\/span><span class=\"o\">.<\/span><span class=\"n\">zeros<\/span><span class=\"p\">(<\/span><span class=\"n\">carkind<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">num_1<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"n\">num<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">carkind<\/span><span class=\"p\">):<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">kC<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">!=<\/span> <span class=\"mi\">0<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">num_1<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">kC<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">):<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">solution<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">==<\/span> <span class=\"mi\">1<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">jud<\/span><span class=\"p\">[<\/span><span class=\"n\">data_1<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]]<\/span> <span class=\"o\">+=<\/span> <span class=\"mi\">1<\/span>\n            <span class=\"n\">num<\/span> <span class=\"o\">+=<\/span> <span class=\"mi\">1<\/span>\n    <span class=\"n\">invalid<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">carkind<\/span><span class=\"p\">):<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">kC<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">!=<\/span> <span class=\"n\">jud<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]:<\/span>\n            <span class=\"n\">invalid<\/span> <span class=\"o\">+=<\/span> <span class=\"mi\">1<\/span>\n    <span class=\"n\">invalid_rate<\/span> <span class=\"o\">=<\/span> <span class=\"mf\">0.0<\/span>\n    <span class=\"n\">invalid_rate<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">float<\/span><span class=\"p\">(<\/span>\n        <span class=\"n\">Decimal<\/span><span class=\"p\">(<\/span><span class=\"nb\">str<\/span><span class=\"p\">((<\/span><span class=\"n\">invalid<\/span> <span class=\"o\">\/<\/span> <span class=\"n\">N<\/span><span class=\"p\">)<\/span> <span class=\"o\">*<\/span> <span class=\"mi\">100<\/span><span class=\"p\">))<\/span><span class=\"o\">.<\/span><span class=\"n\">quantize<\/span><span class=\"p\">(<\/span>\n            <span class=\"n\">Decimal<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"0.1\"<\/span><span class=\"p\">),<\/span> <span class=\"n\">rounding<\/span><span class=\"o\">=<\/span><span class=\"n\">ROUND_HALF_UP<\/span>\n        <span class=\"p\">)<\/span>\n    <span class=\"p\">)<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">invalid_rate<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"c1\"># \u8272\u306e\u5207\u308a\u66ff\u3048\u56de\u6570\u306e\u5224\u65ad\u3092\u3059\u308bcolor_switch\u95a2\u6570<\/span>\n<span class=\"k\">def<\/span> <span class=\"nf\">color_switch<\/span><span class=\"p\">(<\/span><span class=\"n\">solution<\/span><span class=\"p\">,<\/span> <span class=\"n\">N<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">switch<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"n\">cur_color<\/span> <span class=\"o\">=<\/span> <span class=\"n\">solution<\/span><span class=\"p\">[<\/span><span class=\"mi\">0<\/span><span class=\"p\">]<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">):<\/span>\n        <span class=\"k\">if<\/span> <span class=\"n\">solution<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">!=<\/span> <span class=\"n\">cur_color<\/span><span class=\"p\">:<\/span>\n            <span class=\"n\">switch<\/span> <span class=\"o\">+=<\/span> <span class=\"mi\">1<\/span>\n            <span class=\"n\">cur_color<\/span> <span class=\"o\">=<\/span> <span class=\"n\">solution<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span>\n    <span class=\"k\">return<\/span> <span class=\"n\">switch<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E6%AF%94%E8%BC%83%E5%AE%9F%E9%A8%93\"><\/span>\u6bd4\u8f03\u5b9f\u9a13<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u5b9f\u969b\u306b\u6bd4\u8f03\u3059\u308b\u305f\u3081\u306b\u30c7\u30fc\u30bf\u306e\u6570\u3092\u5897\u3084\u3057\u3066\u5b9f\u9a13\u3092\u884c\u306a\u3063\u3066\u3044\u304f\u3002<br>\u30c7\u30fc\u30bf\u306e\u6570\u306f2\u53f0\u305a\u3064\u5897\u3084\u3057\u300110~100\u53f0\u307e\u3067\u306e\u6700\u9069\u5316\u3092\u884c\u306a\u3063\u305f\u3002<br>\u307e\u305f\u3001\u3053\u306e\u6700\u9069\u5316\u30925\u56de\u7e70\u308a\u8fd4\u3057\u89e3\u304f\u3002<\/p>\n<p>\u5b9f\u9a13\u306b\u7528\u3044\u308b\u8eca\u306e\u8eca\u7a2e\u306f\u3001\u8ad6\u6587\u3067\u306f121\u7a2e\u985e\u3060\u3063\u305f\u306e\u3067\u3053\u3053\u3067\u3082\u305d\u308c\u3092\u63a1\u7528\u3059\u308b\u3002<\/p>\n<p>\u307e\u305f\u3001Gurobi Optimizer\u3068\u3044\u3046\u6700\u9069\u5316\u30c4\u30fc\u30eb\u3092\u4f7f\u3063\u3066\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3084\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306a\u3069\u306e\u89e3\u304cGurobi\u306e\u5c0e\u304d\u51fa\u3059\u6700\u9069\u89e3\u3068\u3069\u308c\u3060\u3051\u5dee\u304c\u3042\u308b\u306e\u304b\u3092\u6bd4\u8f03\u3059\u308b\u3002<\/p>\n<p>\u3053\u306e\u6bd4\u8f03\u5b9f\u9a13\u3067\u306f\u3001\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u3068\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u305d\u308c\u305e\u308c\u306b\u304b\u304b\u308b\u6642\u9593\u306e\u6e2c\u5b9a\u3082\u884c\u306a\u3063\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"kn\">import<\/span> <span class=\"nn\">time<\/span>\n<span class=\"kn\">import<\/span> <span class=\"nn\">gurobipy<\/span> <span class=\"k\">as<\/span> <span class=\"nn\">gp<\/span>\n<span class=\"kn\">from<\/span> <span class=\"nn\">gurobipy<\/span> <span class=\"kn\">import<\/span> <span class=\"n\">GRB<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"c1\"># \u4e8c\u3064\u306e\u65b9\u6cd5\u3092\u30c7\u30fc\u30bf\u91cf\u3092\u5909\u3048\u3066\u6027\u80fd\u6bd4\u8f03\u3059\u308b<\/span>\n\n<span class=\"c1\"># \u30c7\u30fc\u30bf\u91cf\u3092\u5165\u308c\u308b\u30ea\u30b9\u30c8(\u30c7\u30fc\u30bf\u91cf\u309210\u53f0\u306e\u5f85\u3061\u884c\u5217\u304b\u30892\u53f0\u305a\u3064\u5897\u3084\u3057\u306a\u304c\u308928\u53f0\u307e\u3067\u8a08\u7b97\u3059\u308b)<\/span>\n<span class=\"n\">N<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">list<\/span><span class=\"p\">(<\/span><span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"mi\">10<\/span><span class=\"p\">,<\/span> <span class=\"mi\">100<\/span><span class=\"p\">,<\/span> <span class=\"mi\">2<\/span><span class=\"p\">))<\/span>\n<span class=\"c1\"># N = [30]<\/span>\n<span class=\"c1\"># 10~28\u53f0\u306e\u5f85\u3061\u884c\u5217\u306e\u6700\u9069\u5316\u3092\u7e70\u308a\u8fd4\u3059\u56de\u6570\uff1aM\u3092\u5b9a\u7fa9\u3059\u308b<\/span>\n<span class=\"n\">M<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">10<\/span>\n<span class=\"n\">carkind<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">121<\/span>\n<span class=\"n\">invalid_rate_bf<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n<span class=\"n\">invalid_rate_sa<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n<span class=\"n\">invalid_rate_gurobi<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n<span class=\"c1\"># \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306e\u5b9a\u7fa9<\/span>\n<span class=\"n\">df_bf_sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">(<\/span><span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"Data volume\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"number of switch times\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"way\"<\/span><span class=\"p\">])<\/span>\n<span class=\"n\">df_sa_sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">(<\/span><span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"Data volume\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"number of switch times\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"way\"<\/span><span class=\"p\">])<\/span>\n<span class=\"n\">df_gurobi_sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">(<\/span><span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"Data volume\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"number of switch times\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"way\"<\/span><span class=\"p\">])<\/span>\n\n<span class=\"k\">for<\/span> <span class=\"n\">m<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">M<\/span><span class=\"p\">):<\/span>\n    <span class=\"n\">bf_sum_cal_time<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"n\">sa_sum_cal_time<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n    <span class=\"n\">data_bf<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"n\">data_sa<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"n\">data_gurobi<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"n\">way_bf<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"n\">way_sa<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"n\">way_gurobi<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n    <span class=\"k\">for<\/span> <span class=\"n\">n<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">N<\/span><span class=\"p\">:<\/span>\n        <span class=\"n\">data_1<\/span><span class=\"p\">,<\/span> <span class=\"n\">NofC<\/span><span class=\"p\">,<\/span> <span class=\"n\">kC<\/span><span class=\"p\">,<\/span> <span class=\"n\">AC<\/span> <span class=\"o\">=<\/span> <span class=\"n\">mkdata<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">,<\/span> <span class=\"n\">carkind<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"c1\"># \u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593\u306e\u8a08\u6e2c<\/span>\n        <span class=\"n\">bf_t1<\/span> <span class=\"o\">=<\/span> <span class=\"n\">time<\/span><span class=\"o\">.<\/span><span class=\"n\">time<\/span><span class=\"p\">()<\/span>\n        <span class=\"n\">bf_solution<\/span> <span class=\"o\">=<\/span> <span class=\"n\">blackfirst<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">,<\/span> <span class=\"n\">carkind<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_1<\/span><span class=\"p\">,<\/span> <span class=\"n\">kC<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">bf_t2<\/span> <span class=\"o\">=<\/span> <span class=\"n\">time<\/span><span class=\"o\">.<\/span><span class=\"n\">time<\/span><span class=\"p\">()<\/span>\n        <span class=\"n\">bf_pre_cal_time<\/span> <span class=\"o\">=<\/span> <span class=\"n\">bf_t2<\/span> <span class=\"o\">-<\/span> <span class=\"n\">bf_t1<\/span>\n        <span class=\"n\">bf_sum_cal_time<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">bf_pre_cal_time<\/span>\n\n        <span class=\"c1\"># \u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593\u306e\u8a08\u6e2c<\/span>\n        <span class=\"n\">sa_t1<\/span> <span class=\"o\">=<\/span> <span class=\"n\">time<\/span><span class=\"o\">.<\/span><span class=\"n\">time<\/span><span class=\"p\">()<\/span>\n        <span class=\"n\">sa_solution<\/span> <span class=\"o\">=<\/span> <span class=\"n\">simulatedannealing<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">,<\/span> <span class=\"n\">carkind<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_1<\/span><span class=\"p\">,<\/span> <span class=\"n\">NofC<\/span><span class=\"p\">,<\/span> <span class=\"n\">kC<\/span><span class=\"p\">,<\/span> <span class=\"n\">AC<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">sa_t2<\/span> <span class=\"o\">=<\/span> <span class=\"n\">time<\/span><span class=\"o\">.<\/span><span class=\"n\">time<\/span><span class=\"p\">()<\/span>\n        <span class=\"n\">sa_pre_cal_time<\/span> <span class=\"o\">=<\/span> <span class=\"n\">sa_t2<\/span> <span class=\"o\">-<\/span> <span class=\"n\">sa_t1<\/span>\n        <span class=\"n\">sa_sum_cal_time<\/span> <span class=\"o\">+=<\/span> <span class=\"n\">sa_pre_cal_time<\/span>\n\n        <span class=\"c1\"># gurobi\u3092\u7528\u3044\u3066\u6700\u9069\u89e3\u3092\u6c42\u3081\u308b<\/span>\n        <span class=\"n\">mcps<\/span> <span class=\"o\">=<\/span> <span class=\"n\">gp<\/span><span class=\"o\">.<\/span><span class=\"n\">Model<\/span><span class=\"p\">(<\/span><span class=\"n\">name<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"MCPS\"<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">s<\/span> <span class=\"o\">=<\/span> <span class=\"p\">{}<\/span>\n        <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">):<\/span>\n            <span class=\"n\">s<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">=<\/span> <span class=\"n\">mcps<\/span><span class=\"o\">.<\/span><span class=\"n\">addVar<\/span><span class=\"p\">(<\/span><span class=\"n\">vtype<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"B\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">name<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"s[<\/span><span class=\"si\">%s<\/span><span class=\"s2\">]\"<\/span> <span class=\"o\">%<\/span> <span class=\"n\">i<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">mcps<\/span><span class=\"o\">.<\/span><span class=\"n\">update<\/span><span class=\"p\">()<\/span>\n        <span class=\"c1\"># \u76ee\u7684\u95a2\u6570<\/span>\n        <span class=\"n\">mcps<\/span><span class=\"o\">.<\/span><span class=\"n\">setObjective<\/span><span class=\"p\">(<\/span>\n            <span class=\"o\">-<\/span><span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">s<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"o\">*<\/span> <span class=\"n\">s<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"nb\">len<\/span><span class=\"p\">(<\/span><span class=\"n\">s<\/span><span class=\"p\">)<\/span> <span class=\"o\">-<\/span> <span class=\"mi\">2<\/span><span class=\"p\">)),<\/span> <span class=\"n\">GRB<\/span><span class=\"o\">.<\/span><span class=\"n\">MINIMIZE<\/span>\n        <span class=\"p\">)<\/span>\n        <span class=\"c1\"># \u5236\u7d04<\/span>\n        <span class=\"k\">for<\/span> <span class=\"n\">l<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">carkind<\/span><span class=\"p\">):<\/span>\n            <span class=\"n\">mcps<\/span><span class=\"o\">.<\/span><span class=\"n\">addConstr<\/span><span class=\"p\">(<\/span><span class=\"n\">kC<\/span><span class=\"p\">[<\/span><span class=\"n\">l<\/span><span class=\"p\">]<\/span> <span class=\"o\">==<\/span> <span class=\"nb\">sum<\/span><span class=\"p\">(<\/span><span class=\"n\">s<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span> <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"n\">AC<\/span><span class=\"p\">[<\/span><span class=\"n\">l<\/span><span class=\"p\">]))<\/span>\n\n        <span class=\"n\">mcps<\/span><span class=\"o\">.<\/span><span class=\"n\">params<\/span><span class=\"o\">.<\/span><span class=\"n\">LogToConsole<\/span> <span class=\"o\">=<\/span> <span class=\"mi\">0<\/span>\n        <span class=\"n\">mcps<\/span><span class=\"o\">.<\/span><span class=\"n\">optimize<\/span><span class=\"p\">()<\/span>\n\n        <span class=\"n\">gurobi_solution<\/span> <span class=\"o\">=<\/span> <span class=\"p\">[]<\/span>\n        <span class=\"k\">for<\/span> <span class=\"n\">i<\/span> <span class=\"ow\">in<\/span> <span class=\"nb\">range<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">):<\/span>\n            <span class=\"k\">if<\/span> <span class=\"n\">s<\/span><span class=\"p\">[<\/span><span class=\"n\">i<\/span><span class=\"p\">]<\/span><span class=\"o\">.<\/span><span class=\"n\">x<\/span> <span class=\"o\">==<\/span> <span class=\"mf\">1.0<\/span><span class=\"p\">:<\/span>\n                <span class=\"n\">gurobi_solution<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"mi\">1<\/span><span class=\"p\">)<\/span>\n            <span class=\"k\">else<\/span><span class=\"p\">:<\/span>\n                <span class=\"n\">gurobi_solution<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"o\">-<\/span><span class=\"mi\">1<\/span><span class=\"p\">)<\/span>\n\n        <span class=\"c1\"># \u305d\u308c\u305e\u308c\u306e\u7d50\u679c\u3092\u30ea\u30b9\u30c8\u306b\u683c\u7d0d\u3059\u308b.<\/span>\n        <span class=\"n\">data_bf<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">color_switch<\/span><span class=\"p\">(<\/span><span class=\"n\">bf_solution<\/span><span class=\"p\">,<\/span> <span class=\"n\">n<\/span><span class=\"p\">))<\/span>\n        <span class=\"n\">data_sa<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">color_switch<\/span><span class=\"p\">(<\/span><span class=\"n\">sa_solution<\/span><span class=\"p\">,<\/span> <span class=\"n\">n<\/span><span class=\"p\">))<\/span>\n        <span class=\"n\">data_gurobi<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">color_switch<\/span><span class=\"p\">(<\/span><span class=\"n\">gurobi_solution<\/span><span class=\"p\">,<\/span> <span class=\"n\">n<\/span><span class=\"p\">))<\/span>\n        <span class=\"n\">invalid_rate_bf<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">judge_ans<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">,<\/span> <span class=\"n\">carkind<\/span><span class=\"p\">,<\/span> <span class=\"n\">bf_solution<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_1<\/span><span class=\"p\">,<\/span> <span class=\"n\">kC<\/span><span class=\"p\">))<\/span>\n        <span class=\"n\">invalid_rate_sa<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">judge_ans<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">,<\/span> <span class=\"n\">carkind<\/span><span class=\"p\">,<\/span> <span class=\"n\">sa_solution<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_1<\/span><span class=\"p\">,<\/span> <span class=\"n\">kC<\/span><span class=\"p\">))<\/span>\n        <span class=\"n\">invalid_rate_gurobi<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"n\">judge_ans<\/span><span class=\"p\">(<\/span><span class=\"n\">n<\/span><span class=\"p\">,<\/span> <span class=\"n\">carkind<\/span><span class=\"p\">,<\/span> <span class=\"n\">gurobi_solution<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_1<\/span><span class=\"p\">,<\/span> <span class=\"n\">kC<\/span><span class=\"p\">))<\/span>\n        <span class=\"n\">way_bf<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"BlackFirst\"<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">way_sa<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"SimulatedAnnealing\"<\/span><span class=\"p\">)<\/span>\n        <span class=\"n\">way_gurobi<\/span><span class=\"o\">.<\/span><span class=\"n\">append<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"gurobi\"<\/span><span class=\"p\">)<\/span>\n    <span class=\"c1\"># \u51fa\u6765\u4e0a\u304c\u3063\u305f\u30c7\u30fc\u30bf\u3092\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306b\u3059\u308b\u3002<\/span>\n    <span class=\"n\">df_bf_tem<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">(<\/span>\n        <span class=\"nb\">list<\/span><span class=\"p\">(<\/span><span class=\"nb\">zip<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_bf<\/span><span class=\"p\">,<\/span> <span class=\"n\">way_bf<\/span><span class=\"p\">)),<\/span>\n        <span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"Data volume\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"number of switch times\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"way\"<\/span><span class=\"p\">],<\/span>\n    <span class=\"p\">)<\/span>\n    <span class=\"n\">df_bf_sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">concat<\/span><span class=\"p\">([<\/span><span class=\"n\">df_bf_sum<\/span><span class=\"p\">,<\/span> <span class=\"n\">df_bf_tem<\/span><span class=\"p\">])<\/span>\n    <span class=\"n\">df_bf_sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">df_bf_sum<\/span><span class=\"o\">.<\/span><span class=\"n\">reset_index<\/span><span class=\"p\">(<\/span><span class=\"n\">drop<\/span><span class=\"o\">=<\/span><span class=\"kc\">True<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">df_sa_tem<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">(<\/span>\n        <span class=\"nb\">list<\/span><span class=\"p\">(<\/span><span class=\"nb\">zip<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_sa<\/span><span class=\"p\">,<\/span> <span class=\"n\">way_sa<\/span><span class=\"p\">)),<\/span>\n        <span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"Data volume\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"number of switch times\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"way\"<\/span><span class=\"p\">],<\/span>\n    <span class=\"p\">)<\/span>\n    <span class=\"n\">df_sa_sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">concat<\/span><span class=\"p\">([<\/span><span class=\"n\">df_sa_sum<\/span><span class=\"p\">,<\/span> <span class=\"n\">df_sa_tem<\/span><span class=\"p\">])<\/span>\n    <span class=\"n\">df_sa_sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">df_sa_sum<\/span><span class=\"o\">.<\/span><span class=\"n\">reset_index<\/span><span class=\"p\">(<\/span><span class=\"n\">drop<\/span><span class=\"o\">=<\/span><span class=\"kc\">True<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">df_gurobi_tem<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">DataFrame<\/span><span class=\"p\">(<\/span>\n        <span class=\"nb\">list<\/span><span class=\"p\">(<\/span><span class=\"nb\">zip<\/span><span class=\"p\">(<\/span><span class=\"n\">N<\/span><span class=\"p\">,<\/span> <span class=\"n\">data_gurobi<\/span><span class=\"p\">,<\/span> <span class=\"n\">way_gurobi<\/span><span class=\"p\">)),<\/span>\n        <span class=\"n\">columns<\/span><span class=\"o\">=<\/span><span class=\"p\">[<\/span><span class=\"s2\">\"Data volume\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"number of switch times\"<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"way\"<\/span><span class=\"p\">],<\/span>\n    <span class=\"p\">)<\/span>\n    <span class=\"n\">df_gurobi_sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">concat<\/span><span class=\"p\">([<\/span><span class=\"n\">df_gurobi_sum<\/span><span class=\"p\">,<\/span> <span class=\"n\">df_gurobi_tem<\/span><span class=\"p\">])<\/span>\n    <span class=\"n\">df_gurobi_sum<\/span> <span class=\"o\">=<\/span> <span class=\"n\">df_gurobi_sum<\/span><span class=\"o\">.<\/span><span class=\"n\">reset_index<\/span><span class=\"p\">(<\/span><span class=\"n\">drop<\/span><span class=\"o\">=<\/span><span class=\"kc\">True<\/span><span class=\"p\">)<\/span>\n    <span class=\"c1\"># \u8a08\u6e2c\u7d50\u679c\u306e\u8868\u793a<\/span>\n    <span class=\"n\">bf_cal_time_min<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">int<\/span><span class=\"p\">(<\/span><span class=\"n\">bf_sum_cal_time<\/span> <span class=\"o\">\/<\/span> <span class=\"mi\">60<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">bf_cal_time_sec<\/span> <span class=\"o\">=<\/span> <span class=\"n\">bf_sum_cal_time<\/span> <span class=\"o\">-<\/span> <span class=\"n\">bf_cal_time_min<\/span> <span class=\"o\">*<\/span> <span class=\"mi\">60<\/span>\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">m<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\":\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">bf_cal_time_sec<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"\u79d2\"<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">sa_cal_time_min<\/span> <span class=\"o\">=<\/span> <span class=\"nb\">int<\/span><span class=\"p\">(<\/span><span class=\"n\">sa_sum_cal_time<\/span> <span class=\"o\">\/<\/span> <span class=\"mi\">60<\/span><span class=\"p\">)<\/span>\n    <span class=\"n\">sa_cal_time_sec<\/span> <span class=\"o\">=<\/span> <span class=\"n\">sa_sum_cal_time<\/span> <span class=\"o\">-<\/span> <span class=\"n\">sa_cal_time_min<\/span> <span class=\"o\">*<\/span> <span class=\"mi\">60<\/span>\n    <span class=\"nb\">print<\/span><span class=\"p\">(<\/span>\n        <span class=\"s2\">\"\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">m<\/span> <span class=\"o\">+<\/span> <span class=\"mi\">1<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\":\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">sa_cal_time_min<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"\u5206\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">sa_cal_time_sec<\/span><span class=\"p\">,<\/span> <span class=\"s2\">\"\u79d2\"<\/span>\n    <span class=\"p\">)<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\">&nbsp;<\/div>\n<div class=\"output_subarea output_stream output_stdout output_text\">\n<pre>\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593 1 : 0.0011627674102783203 \u79d2\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593 1 : 1 \u5206 36.8944628238678 \u79d2\n\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593 2 : 0.0011641979217529297 \u79d2\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593 2 : 1 \u5206 36.58262491226196 \u79d2\n\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593 3 : 0.0011982917785644531 \u79d2\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593 3 : 1 \u5206 35.92641258239746 \u79d2\n\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593 4 : 0.0011830329895019531 \u79d2\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593 4 : 1 \u5206 35.00624179840088 \u79d2\n\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593 5 : 0.0011432170867919922 \u79d2\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593 5 : 1 \u5206 36.09841275215149 \u79d2\n\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593 6 : 0.0011780261993408203 \u79d2\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593 6 : 1 \u5206 35.69149589538574 \u79d2\n\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593 7 : 0.0011763572692871094 \u79d2\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593 7 : 1 \u5206 35.610944986343384 \u79d2\n\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593 8 : 0.0011775493621826172 \u79d2\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593 8 : 1 \u5206 34.82879114151001 \u79d2\n\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593 9 : 0.001186370849609375 \u79d2\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593 9 : 1 \u5206 34.53449368476868 \u79d2\n\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u304b\u304b\u308b\u6642\u9593 10 : 0.0011332035064697266 \u79d2\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593 10 : 1 \u5206 36.17280316352844 \u79d2\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u3068\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u6bd4\u8f03\u5b9f\u9a13\u3092\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u305f\u3002<\/p>\n<p>\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306b\u304b\u304b\u308b\u6642\u9593\u306f\u7d041\u5206\u534a\u3068\u304b\u306a\u308a\u9577\u3044\u3082\u306e\u3068\u306a\u3063\u305f\u3002\u3055\u3089\u306b\u3001\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306f\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u6bd4\u3079\u3001\u7d048\u4e07\u500d\u306e\u6642\u9593\u3092\u304b\u3051\u3066\u8a08\u7b97\u3092\u884c\u306a\u3063\u3066\u3044\u308b\u3053\u3068\u304c\u308f\u304b\u3063\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"c1\"># \u7d50\u679c\u3092\u30b0\u30e9\u30d5\u306b\u8868\u793a\u3059\u308b\u305f\u3081\u306b\u3001\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306e\u7d50\u679c\u3068\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u7d50\u679c\u3092\u5408\u308f\u305b\u308b<\/span>\n<span class=\"n\">df<\/span> <span class=\"o\">=<\/span> <span class=\"n\">pd<\/span><span class=\"o\">.<\/span><span class=\"n\">concat<\/span><span class=\"p\">([<\/span><span class=\"n\">df_bf_sum<\/span><span class=\"p\">,<\/span> <span class=\"n\">df_sa_sum<\/span><span class=\"p\">,<\/span> <span class=\"n\">df_gurobi_sum<\/span><span class=\"p\">])<\/span>\n<span class=\"n\">df<\/span> <span class=\"o\">=<\/span> <span class=\"n\">df<\/span><span class=\"o\">.<\/span><span class=\"n\">reset_index<\/span><span class=\"p\">(<\/span><span class=\"n\">drop<\/span><span class=\"o\">=<\/span><span class=\"kc\">True<\/span><span class=\"p\">)<\/span>\n<span class=\"c1\"># \u30c7\u30fc\u30bf\u91cf\u306b\u5bfe\u3059\u308b\u8272\u306e\u5207\u308a\u66ff\u3048\u56de\u6570\u3092\u30b0\u30e9\u30d5\u306b\u3059\u308b<\/span>\n<span class=\"n\">sns<\/span><span class=\"o\">.<\/span><span class=\"n\">relplot<\/span><span class=\"p\">(<\/span>\n    <span class=\"n\">x<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"Data volume\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">y<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"number of switch times\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">hue<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"way\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">style<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"way\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">kind<\/span><span class=\"o\">=<\/span><span class=\"s2\">\"line\"<\/span><span class=\"p\">,<\/span>\n    <span class=\"n\">data<\/span><span class=\"o\">=<\/span><span class=\"n\">df<\/span><span class=\"p\">,<\/span>\n<span class=\"p\">)<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<div id=\"attachment_3876\" style=\"width: 488px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-3876\" src=\"\/T-Wave\/wp-content\/uploads\/2022\/07\/download.png\" alt=\"\u56f32:\u30c7\u30fc\u30bf\u30b5\u30a4\u30ba\u306b\u5bfe\u3059\u308b\u5857\u88c5\u3059\u308b\u8272\u306e\u5207\u308a\u66ff\u3048\u56de\u6570\" width=\"478\" height=\"352\" class=\"wp-image-3876 size-full\"><p id=\"caption-attachment-3876\" class=\"wp-caption-text\">\u56f32:\u30c7\u30fc\u30bf\u30b5\u30a4\u30ba\u306b\u5bfe\u3059\u308b\u5857\u88c5\u3059\u308b\u8272\u306e\u5207\u308a\u66ff\u3048\u56de\u6570<\/p><\/div><p><\/p>\n<p>\u30b0\u30e9\u30d5\u304b\u3089\u3001\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u65b9\u304c\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u6bd4\u3079\u3066\u8272\u306e\u5207\u308a\u66ff\u3048\u56de\u6570\u3092\u5c11\u306a\u304f\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u3066\u3044\u308b\u3053\u3068\u304c\u308f\u304b\u308b\u3002\u305d\u308c\u306b\u5bfe\u3057\u3066Gurobi\u306e\u89e3\u306f\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306b\u6bd4\u3079\u3066\u5207\u308a\u66ff\u3048\u56de\u6570\u3092\u5c11\u306a\u304f\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u3066\u304a\u308a\u3001\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3068\u6bd4\u3079\u3066\u3082\u30c7\u30fc\u30bf\u30b5\u30a4\u30ba\u304c25\u4ee5\u4e0b\u3067\u306f\u540c\u7a0b\u5ea6\u306e\u5207\u308a\u66ff\u3048\u56de\u6570\u3060\u3063\u305f\u304c\u3001\u305d\u308c\u4ee5\u964d\u306fGurobi\u306e\u65b9\u304c\u5207\u308a\u66ff\u3048\u56de\u6570\u306e\u5c11\u306a\u3044\u89e3\u3092\u51fa\u3059\u3053\u3068\u304c\u3067\u304d\u3066\u3044\u308b\u3002<br>\u6b21\u306b\u3001\u5236\u7d04\u3092\u6e80\u305f\u3057\u3066\u3044\u308b\u304b\u306e\u5224\u65ad\u3092\u884c\u3046\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing code_cell rendered\">\n<div class=\"input\">\n<div class=\"inner_cell\">\n<div class=\"input_area\">\n<div class=\" highlight hl-python\">\n<pre><span class=\"c1\"># \u5236\u7d04\u3092\u6e80\u305f\u3057\u3066\u3044\u308b\u304b\u306e\u78ba\u8a8d\u3092\u884c\u3046\u3002<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u304c\u5236\u7d04\u3092\u7834\u3063\u305f\u5272\u5408:\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">invalid_rate_bf<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u304c\u5236\u7d04\u3092\u7834\u3063\u305f\u5272\u5408:\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">invalid_rate_sa<\/span><span class=\"p\">)<\/span>\n<span class=\"nb\">print<\/span><span class=\"p\">(<\/span><span class=\"s2\">\"gurobi\u304c\u5236\u7d04\u3092\u7834\u3063\u305f\u5272\u5408\"<\/span><span class=\"p\">,<\/span> <span class=\"n\">invalid_rate_gurobi<\/span><span class=\"p\">)<\/span>\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"output_wrapper\">\n<div class=\"output\">\n<div class=\"output_area\">\n<div class=\"prompt\">&nbsp;<\/div>\n<div class=\"output_subarea output_stream output_stdout output_text\">\n<pre>\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u304c\u5236\u7d04\u3092\u7834\u3063\u305f\u5272\u5408: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u304c\u5236\u7d04\u3092\u7834\u3063\u305f\u5272\u5408: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\ngurobi\u304c\u5236\u7d04\u3092\u7834\u3063\u305f\u5272\u5408 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>invarid_rate_bf, sa, Gurobi\u306f\u3068\u3082\u306b\u305d\u308c\u305e\u308c\u306e\u89e3\u306b\u3064\u3044\u3066nxm\u56de\u76ee([latex]n\\in N, m\\in M[\/latex], [latex]N[\/latex]\u306f\u554f\u984c\u30b5\u30a4\u30ba\u3001[latex]M[\/latex]\u306f\u5b9f\u9a13\u306e\u8a66\u884c\u56de\u6570)\u306b\u304a\u3044\u3066\u3001\u6ce8\u6587\u306e\u5236\u7d04\u3092\u6e80\u305f\u3057\u3066\u3044\u308b\u5272\u5408\u3092\u793a\u3057\u3066\u3044\u308b\u3002\u3069\u3061\u3089\u3082\u30ea\u30b9\u30c8\u306e\u5185\u5bb9\u306f\u5168\u30660.0\u3068\u306a\u3063\u3066\u3044\u308b\u306e\u3067\u3001\u5236\u7d04\u304c\u6e80\u305f\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u304c\u308f\u304b\u308b\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E7%B5%90%E8%AB%96\"><\/span>\u7d50\u8ad6<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u4eca\u56de\u3001\u81ea\u4f5c\u3057\u305f\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u3088\u3063\u3066\u3001\u554f\u984c\u306e\u4f5c\u6210\u3092\u884c\u3044\u3001\u305d\u308c\u30922\u7a2e\u985e\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u5b9f\u88c5\u3059\u308b\u3053\u3068\u306b\u3088\u3063\u3066\u89e3\u304f\u3053\u3068\u304c\u3067\u304d\u305f\u3002<\/p>\n<p>\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u306e\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u3001\u8caa\u6b32\u306b\u5857\u88c5\u3059\u308b\u8272\u3092\u5272\u308a\u632f\u308b\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3068\u3057\u3066\u3001\u5236\u7d04\u3092\u6e80\u305f\u3057\u306a\u304c\u3089\u89e3\u3092\u5c0e\u51fa\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u305f\u3002<\/p>\n<p>\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3067\u306f\u6ce8\u6587\u306e\u5236\u7d04\u3092\u6e80\u305f\u3057\u306a\u304c\u3089\u89e3\u306e\u63a2\u7d22\u3092\u884c\u3044\u3001MCPS\u554f\u984c\u3092\u89e3\u304f\u3053\u3068\u304c\u3067\u304d\u305f\u3002<\/p>\n<p>\u7d50\u679c\u306f\u8ad6\u6587\u3068\u540c\u69d8\u306b\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u3068\u6bd4\u8f03\u3057\u3066\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u3067\u306f\u8272\u306e\u5207\u308a\u66ff\u3048\u56de\u6570\u306e\u5c11\u306a\u3044\u89e3\u3092\u5c0e\u304f\u3053\u3068\u304c\u3067\u304d\u305f\u3002<br>\u3057\u304b\u3057\u3001\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u5c0e\u304d\u51fa\u3057\u305f\u89e3\u306f\u3001\u554f\u984c\u30b5\u30a4\u30ba\u304c\u5927\u304d\u304f\u306a\u308b\u307b\u3069Gurobi\u304c\u5c0e\u3044\u305f\u6700\u9069\u89e3\u306b\u6bd4\u3079\u3066\u5207\u308a\u66ff\u3048\u56de\u6570\u306e\u591a\u3044\u89e3\u3068\u306a\u3063\u3066\u3057\u307e\u3063\u305f\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<h2><span class=\"ez-toc-section\" id=\"%E3%81%82%E3%81%A8%E3%81%8C%E3%81%8D\"><\/span>\u3042\u3068\u304c\u304d<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"cell border-box-sizing text_cell rendered\">\n<div class=\"inner_cell\">\n<div class=\"text_cell_render border-box-sizing rendered_html\">\n<p>\u8ad6\u6587\u306e\u7d50\u679c\u3068\u540c\u69d8\u306b\u3001\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u65b9\u304c\u8caa\u6b32\u6cd5\u3067\u3042\u308b\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u3088\u308a\u3082\u8272\u306e\u5207\u308a\u66ff\u3048\u56de\u6570\u3092\u6e1b\u3089\u3057\u305f\u89e3\u3092\u51fa\u3059\u3053\u3068\u304c\u3067\u304d\u308b\u306e\u3092\u78ba\u8a8d\u3067\u304d\u305f\u3002<br>\u4eca\u5f8c\u306e\u5c55\u671b\u3068\u3057\u3066\u306f\u3001\u91cf\u5b50\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u30de\u30b7\u30f3\u3067\u306e\u5b9f\u88c5\u3082\u884c\u3063\u3066\u307f\u3066\u3001\u672c\u5b9f\u9a13\u3067\u4f7f\u3063\u305f2\u7a2e\u985e\u306e\u624b\u6cd5\u3068\u306e\u6bd4\u8f03\u3092\u884c\u3063\u3066\u307f\u305f\u3044\u3068\u601d\u3063\u305f\u3002\u307e\u305f\u3001\u3053\u306e\u554f\u984c\u306f2\u7a2e\u985e\u306e\u5857\u308a\u5206\u3051\u3060\u3063\u305f\u304c\u30013\u7a2e\u985e\u4ee5\u4e0a\u306e\u5857\u308a\u5206\u3051\u306b\u5bfe\u5fdc\u3057\u305f\u30d7\u30ed\u30b0\u30e9\u30e0\u3082\u4f5c\u6210\u3057\u3066\u307f\u305f\u3044\u3068\u611f\u3058\u305f.<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n<h2><span class=\"ez-toc-section\" id=\"%E6%8B%85%E5%BD%93%E8%80%85\"><\/span>\u62c5\u5f53\u8005<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u5e73\u9593\u8349\u592a (\u30e1\u30f3\u30bf\u30ea\u30f3\u30b0\uff1a\u4e38\u5c71\u5c1a\u8cb4\u3001\u7fbd\u5834\u5ec9\u4e00\u90ce)<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u30de\u30eb\u30c1\u30ab\u30fc\u30da\u30a4\u30f3\u30c8\u30b7\u30e7\u30c3\u30d7\u554f\u984c\u306b\u304a\u3044\u3066\u3001\u30d6\u30e9\u30c3\u30af\u30d5\u30a1\u30fc\u30b9\u30c8\u3068\u30b7\u30df\u30e5\u30ec\u30fc\u30c6\u30c3\u30c9\u30a2\u30cb\u30fc\u30ea\u30f3\u30b0\u306e\u5b9f\u88c5\u5b9f\u9a13\u3092\u884c\u3044\u3001\u7d50\u679c\u3092\u6bd4\u8f03\u3057\u305f\u3002<\/p>\n","protected":false},"author":13,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[10,11,13,32,44,56,58,70,75,112],"class_list":["post-3681","post","type-post","status-publish","format-standard","hentry","category-hands-on","tag-d-wave","tag-d-wave-2000q","tag-d-wave-advantage","tag-qbsolv","tag-volkswagen","tag-56","tag-58","tag-70","tag-75","tag-112"],"yoast_head":"<!-- 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