Greedy Genetic Algorithms for Symmetric and Asymmetric TSPs

• Item type: Trans(1)
• 公開日: 2002-11-15
• タイトル: Greedy Genetic Algorithms for Symmetric and Asymmetric TSPs
• タイトル / 言語: en
• タイトル: Greedy Genetic Algorithms for Symmetric and Asymmetric TSPs
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: オリジナル論文
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Graduate School Miyazaki University
• 著者所属: Faculty of Engineering Miyazaki University
• 著者所属: Faculty of Engineering Miyazaki University
• 著者所属: Institute of Information Sciences and Electronics University of Tsukuba
• 著者所属(英): en
• 著者所属(英): Graduate School, Miyazaki University
• 著者所属(英): en
• 著者所属(英): Faculty of Engineering, Miyazaki University
• 著者所属(英): en
• 著者所属(英): Faculty of Engineering, Miyazaki University
• 著者所属(英): en
• 著者所属(英): Institute of Information Sciences and Electronics, University of Tsukuba
• 著者名: HUNGDINHNGUYEN; IKUO, YOSHIHARA; KUNIHITO, YAMAMORI; MORITOSHI, YASUNAGA
• 著者名(英): Hung, DinhNguyen; Ikuo, Yoshihara; Kunihito, Yamamori; Moritoshi, Yasunaga
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This paper presents new enhancements to a multi-population GENITOR-type Genetic Al-gorithm (GA)for solving symmetric and asymmetric Traveling Salesman Problems (TSPs). First improvements to the greedy subtour crossover are proposed so that it works more effectively at the stage of highly t individuals.Next local search heuristics are combined with GA to compensate for its lack of local search ability.The powerful Lin-Kernighan heuristic is used for symmetric TSPs and the fast 3-Opt heuristic is used for asymmetric TSPs. Various symmetric and asymmetric TSP benchmarks taken from the TSPLIB are used to validate the method.Experimental results show that the proposed method can nd optimal solutions for problems ranging in size up to 3795 cities in a reasonable computing time. From the viewpoint of quality of solution these results are the best so far obtained by applyingGA to the TSP.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This paper presents new enhancements to a multi-population GENITOR-type Genetic Al-gorithm (GA)for solving symmetric and asymmetric Traveling Salesman Problems (TSPs). First,improvements to the greedy subtour crossover are proposed so that it works more effectively at the stage of highly t individuals.Next,local search heuristics are combined with GA to compensate for its lack of local search ability.The powerful Lin-Kernighan heuristic is used for symmetric TSPs and the fast 3-Opt heuristic is used for asymmetric TSPs. Various symmetric and asymmetric TSP benchmarks taken from the TSPLIB are used to validate the method.Experimental results show that the proposed method can nd optimal solutions for problems ranging in size up to 3795 cities in a reasonable computing time. From the viewpoint of quality of solution,these results are the best so far obtained by applyingGA to the TSP.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA11464803
• 書誌情報: 情報処理学会論文誌数理モデル化と応用（TOM）; 巻 43, 号 SIG10(TOM7), p. 165-175, 発行日 2002-11-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7780
• 出版者 / 言語: ja
• 出版者: 情報処理学会