{"created":"2023-05-15T12:23:48.634778+00:00","id":15553,"links":{},"metadata":{"_buckets":{"deposit":"f3fed7be-a1f0-4fbc-99c7-d2465ade7459"},"_deposit":{"created_by":10,"id":"15553","owners":[10],"pid":{"revision_id":0,"type":"depid","value":"15553"},"status":"published"},"_oai":{"id":"oai:kansai-u.repo.nii.ac.jp:00015553","sets":["528:1588:1589:1591"]},"author_link":["38709","38708","37037","38707"],"item_9_alternative_title_20":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"Solving Combinatorial Optimization Problems Using Deep Learning"}]},"item_9_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2019-02-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicPageEnd":"659","bibliographicPageStart":"651","bibliographicVolumeNumber":"60","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}]}]},"item_9_description_4":{"attribute_name":"概要","attribute_value_mlt":[{"subitem_description":"本論文では代表的な組合せ最適化問題の1つである巡回セールスマン問題 (TSP) に注目し，深層学習を適用した解法を提案する．本手法では，畳み込みニューラルネットワークを用いて最適経路を画像として学習することで，最適経路に含まれうる辺の分布である優良エッジ分布を求め，これにより計算される辺の評価値である優良エッジ値を利用して近傍探索を行う．この提案手法の性能を調べるために実験を行い，解の精度向上において有効であることを示す．","subitem_description_type":"Other"},{"subitem_description":"In this paper, we focus on the traveling salesman problem (TSP) that is a typical combinatorial optimization problem, and propose a method for solving it with applying deep learning. This method features learning the image of the optimal tour by a convolutional neural network to acquire the Good-Edge Distribution whose edges could be included in the optimal solution. It also conducts neighborhood search by using Good-Edge Value that is an evaluation of each edge calculated from the distribution. We show experimentally that this method improves the quality of solutions.","subitem_description_type":"Other"}]},"item_9_description_5":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"本研究の一部は，JSPS科研費18K11484と，JSPS科研費17K01309，関西大学大学院理工学研究科高度化推進研究費，関西大学先端科学技術推進機構「緊急救命避難支援のための情報通信技術に関する研究開発」研究グループの助成をうけている．","subitem_description_type":"Other"}]},"item_9_full_name_3":{"attribute_name":"著者別名","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"38708","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Miki, Shoma"}]},{"nameIdentifiers":[{"nameIdentifier":"38709","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Ebara, Hiroyuki"}]}]},"item_9_publisher_34":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会"}]},"item_9_rights_13":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"情報処理学会"},{"subitem_rights":"ここに掲載した著作物の利用に関する注意 本著作物の著作権は情報処理学会に帰属します。本著作物は著作権者である情報処理学会の許可のもとに掲載するものです。ご利用に当たっては「著作権法」ならびに「情報処理学会倫理綱領」に従うことをお願いいたします。"}]},"item_9_source_id_10":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","subitem_source_identifier_type":"NCID"}]},"item_9_source_id_8":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"18827764","subitem_source_identifier_type":"ISSN"}]},"item_9_version_type_17":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"三木, 彰馬"}],"nameIdentifiers":[{"nameIdentifier":"38707","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"榎原, 博之"}],"nameIdentifiers":[{"nameIdentifier":"37037","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"50194014","nameIdentifierScheme":"e-Rad","nameIdentifierURI":"https://nrid.nii.ac.jp/ja/nrid/1000050194014"},{"nameIdentifier":"0000-0002-0725-3495","nameIdentifierScheme":"ORCID iD","nameIdentifierURI":"https://orcid.org/0000-0002-0725-3495"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2020-03-19"}],"displaytype":"detail","filename":"KU-1100-20190215-00.pdf","filesize":[{"value":"931.3 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"KU-1100-20190215-00.pdf","url":"https://kansai-u.repo.nii.ac.jp/record/15553/files/KU-1100-20190215-00.pdf"},"version_id":"aecb011e-bf89-4499-9acb-c76e87c8e570"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"組合せ最適化問題","subitem_subject_scheme":"Other"},{"subitem_subject":"巡回セールスマン問題","subitem_subject_scheme":"Other"},{"subitem_subject":"深層学習","subitem_subject_scheme":"Other"},{"subitem_subject":"畳み込みニューラルネットワーク","subitem_subject_scheme":"Other"},{"subitem_subject":"近傍探索法","subitem_subject_scheme":"Other"},{"subitem_subject":"combinatorial optimization problem","subitem_subject_scheme":"Other"},{"subitem_subject":"traveling salesman problem","subitem_subject_scheme":"Other"},{"subitem_subject":"deep learning","subitem_subject_scheme":"Other"},{"subitem_subject":"convolutional neural network","subitem_subject_scheme":"Other"},{"subitem_subject":"neighborhood search","subitem_subject_scheme":"Other"},{"subitem_subject":"関西大学","subitem_subject_scheme":"Other"},{"subitem_subject":"Kansai University","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"深層学習を用いた巡回セールスマン問題の解法","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"深層学習を用いた巡回セールスマン問題の解法"}]},"item_type_id":"9","owner":"10","path":["1591"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-03-19"},"publish_date":"2020-03-19","publish_status":"0","recid":"15553","relation_version_is_last":true,"title":["深層学習を用いた巡回セールスマン問題の解法"],"weko_creator_id":"10","weko_shared_id":-1},"updated":"2023-05-17T02:22:31.907975+00:00"}