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遺伝的交叉を用いた並列シミュレーテッドアニーリングの検討
http://hdl.handle.net/2237/00029181
http://hdl.handle.net/2237/00029181991ffb60-5f87-4b62-b85e-89dfa0a4a754
名前 / ファイル | ライセンス | アクション |
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2018-12-28 | |||||
タイトル | ||||||
タイトル | 遺伝的交叉を用いた並列シミュレーテッドアニーリングの検討 | |||||
言語 | ja | |||||
その他のタイトル | ||||||
その他のタイトル | Examination of Parallel Simulated Annealing using Genetic Crossover | |||||
言語 | en | |||||
著者 |
小掠, 真貴
× 小掠, 真貴× 廣安, 知之× 三木, 光範× 角, 美智子× 岡本, 祐幸× OGURA, Maki× HIROYASU, Tomoyuki× MIKI, Mitsunori× SUMI, Michiko× OKAMOTO, Yuko |
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アクセス権 | ||||||
アクセス権 | open access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||
権利 | ||||||
言語 | ja | |||||
権利情報 | 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。Notice for the use of this material The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). This material is published on this web site with the agreement of the author (s) and the IPSJ. Please be complied with Copyright Law of Japan and the Code of Ethics of the IPSJ if any users wish to reproduce, make derivative work, distribute or make available to the public any part or whole thereof. All Rights Reserved, Copyright (C) Information Processing Society of Japan. Comments are welcome. Mail to address editj@ipsj.or.jp, please. | |||||
抄録 | ||||||
内容記述 | 本研究では,遺伝的交叉を用いた並列シミュレーテッドアニーリング(PSA/GAc)を提案する.PSA/GAcは,複数のプロセス上で並列にシミュレーテッドアニーリングの操作を行い,一定期間のアニーリングを行った後,2プロセス間で遺伝的アルゴリズムのオペレータである交叉により情報交換を行う.これにより,大局的にはいくつかの準最適解が存在し,局所的には無数の準最適解を有するような問題に特に有効であると考えられる.数種のテスト関数に適用した結果,PSA/GAcの優れた性能が明らかとなった.また,実問題への適用例として最適化問題の一つであるタンパク質の構造解析を行い,従来用いられていた手法と比較し,PSA/GAcの有効性を検討した. | |||||
言語 | ja | |||||
内容記述タイプ | Abstract | |||||
抄録 | ||||||
内容記述 | This paper proposes Parallel Simulated Annealing using Genetic Crossover (PSA/GAc). In this algorithm, there are several processes of simulated annealing (SA) working parallel. To exchange information between the solutions, the operation of genetic crossover is performed. Through the continuous test problems, it is found that PSA/GAc can search the solution effectively. The proposed algorithm is also applied to the protein folding problem. Comparing PSA/GAc to the conventional algorithm, it is also found that PSA/GAc is effective algorithm for real world problems. | |||||
言語 | en | |||||
内容記述タイプ | Abstract | |||||
出版者 | ||||||
言語 | ja | |||||
出版者 | 一般社団法人情報処理学会 | |||||
言語 | ||||||
言語 | jpn | |||||
資源タイプ | ||||||
資源タイプresource | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
出版タイプ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
関連情報 | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | URI | |||||
関連識別子 | http://id.nii.ac.jp/1001/00033511/ | |||||
ISSN(print) | ||||||
収録物識別子タイプ | PISSN | |||||
収録物識別子 | 0919-6072 | |||||
書誌情報 |
ja : 情報処理学会研究報告数理モデル化と問題解決(MPS) 巻 2001, 号 27(2000-MPS-033), p. 57-60, 発行日 2001-03 |
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著者版フラグ | ||||||
値 | publisher |