{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00033419","sets":["1164:2735:2772:2774"]},"path":["2774"],"owner":"1","recid":"33419","title":["集中多段交叉を用いた並列分散遺伝的アルゴリズムによる　離散的最適化問題の解法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2002-09-20"},"_buckets":{"deposit":"ea911cdf-58ac-454d-88bf-3ecb6e0db702"},"_deposit":{"id":"33419","pid":{"type":"depid","value":"33419","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"集中多段交叉を用いた並列分散遺伝的アルゴリズムによる　離散的最適化問題の解法","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"集中多段交叉を用いた並列分散遺伝的アルゴリズムによる　離散的最適化問題の解法"},{"subitem_title":"Parallel Distributed GA with Centralized Multiple Crossover Applied to Discrete Optimization Problems","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2002-09-20","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"同志社大学大学院"},{"subitem_text_value":"同志社大学工学部"},{"subitem_text_value":"同志社大学工学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Engineering, Doshisha University","subitem_text_language":"en"},{"subitem_text_value":"Knowledge Engineering Dept., Doshisha University","subitem_text_language":"en"},{"subitem_text_value":"Knowledge Engineering Dept., Doshisha University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/33419/files/IPSJ-MPS02041003.pdf"},"date":[{"dateType":"Available","dateValue":"2004-09-20"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS02041003.pdf","filesize":[{"value":"828.1 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"6706047c-668d-4c67-9e1a-a64e6d02f1cf","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2002 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"水田, 伯典"},{"creatorName":"三木, 光範"},{"creatorName":"廣安, 知之"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takanori, Mizuta","creatorNameLang":"en"},{"creatorName":"Mitsunori, Miki","creatorNameLang":"en"},{"creatorName":"Tomoyuki, Hiroyasu","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"並列分散遺伝的アルゴリズム(PDGA)は，連続最適化問題において良好な性能を示すことが報告されているが，離散的最適化問題に関する報告は少ない．そこで，本研究では離散的最適化問題の中からジョブショ{}ップスケジューリング問題(JSP)を対象としてPDGAの性能を検証し，離散的最適化問題に対して有効な新手法の提案を行う．提案手法は，各島のエリート個体に対して交叉を連続して行う点，および移住操作を行わない点に特徴がある．JSPに対する数値実験の結果，提案手法は高い性能を示した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"This paper proposes a new method of genetic algorithms (GAs) for discrete optimization problems. For discrete optimization problems, the performance of Parallel Distributed GAs (PDGAs) is not so good. We propose a method of increasing the performance of PDGAs. The features of the proposed method are multiple crossover operations applied to the elite genes and DGA without migration. The experiments on Job-shop Schedule Problems showed that the proposed method has a better performance than the conventional GAs, and the method provides an efficient parallel scheme in GAs for discrete optimization problems.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"12","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"9","bibliographicIssueDates":{"bibliographicIssueDate":"2002-09-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"89(2002-MPS-041)","bibliographicVolumeNumber":"2002"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"id":33419,"updated":"2025-01-22T15:42:19.279852+00:00","links":{},"created":"2025-01-18T23:02:15.810811+00:00"}