{"id":203701,"updated":"2025-01-19T20:28:27.039292+00:00","links":{},"created":"2025-01-19T01:06:02.896982+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00203701","sets":["1164:4402:10098:10156"]},"path":["10156"],"owner":"44499","recid":"203701","title":["マルチエージェントシミュレーションを利用したごみ収集作業の最適化"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-02-29"},"_buckets":{"deposit":"d84da03b-feb0-43a0-aade-e50d1053338e"},"_deposit":{"id":"203701","pid":{"type":"depid","value":"203701","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"マルチエージェントシミュレーションを利用したごみ収集作業の最適化","author_link":["502931","502935","502936","502932","502934","502930","502933","502929"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"マルチエージェントシミュレーションを利用したごみ収集作業の最適化"},{"subitem_title":"Optimization of a Refuse Collection by Multi Agent Simulation","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2020-02-29","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"札幌市立大学"},{"subitem_text_value":"札幌市立大学"},{"subitem_text_value":"札幌市立大学"},{"subitem_text_value":"札幌市立大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Sapporo City University","subitem_text_language":"en"},{"subitem_text_value":"Sapporo City University","subitem_text_language":"en"},{"subitem_text_value":"Sapporo City University","subitem_text_language":"en"},{"subitem_text_value":"Sapporo City 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 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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_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-885X","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"地方公共サービスの 1 つであるごみ収集作業では，近年の少子高齢化に伴う従事者の不足と，人件費などの高騰による経費の増加が課題となっている．我々は，時間・ルートを固定せずに乗合車輌の配車決定を行うためのサービスである SAVS（Smart Access Vehicle System）をごみ収集作業へ応用し，ごみ収集ルートおよび搬送車輌数の最適化を目指している．そのために，本研究では，まず SAVS を用いてマルチエージェントシミュレーションを行い，搬送車輌数及びごみの積込み時間が各ごみ収集車輌の総走行時間に与える影響を調べた．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告知能システム（ICS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2020-02-29","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"14","bibliographicVolumeNumber":"2020-ICS-198"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}