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Study on Effect of MOGA with Interactive Island Model using Visualization
http://hdl.handle.net/2237/14440
http://hdl.handle.net/2237/144407f13152b-a646-4c46-80a2-d41adc853dd0
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1052.pdf (1.1 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2011-02-07 | |||||
タイトル | ||||||
タイトル | Study on Effect of MOGA with Interactive Island Model using Visualization | |||||
言語 | en | |||||
著者 |
Yamamoto, Masafumi
× Yamamoto, Masafumi× Yoshikawa, Tomohiro× Furuhashi, Takeshi |
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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 | en | |||||
権利情報 | © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||
抄録 | ||||||
内容記述 | Genetic Algorithm is one of the most effective optimization algorithms, on which a lot of studies have been reported. Some studies on the application of island model, which is one of the representative methods to keep a diversity of solutions, to Multi-Objective Genetic Algorithm (MOGA) have been conducted. In MOGA, it is difficult to find the solutions which satisfy all objective functions because of their tradeoff. Especially when there are many objective functions, it is obvious that it needs a lot of time to search for effective Pareto solutions and find them. This paper proposes the interactive way of addition and deletion of islands to the original ones based on user's requirements with the visualization of acquired solutions in island model for MOGA. This paper applies the proposed method to Nurse Scheduling Problem (NSP) using the visualization by Principal Component Analysis (PCA). Through the experiment, it is confirmed that an interactive tuning of the weights for the objective functions leaded to the acquisition of better Pareto solutions which a user wants while they are difficult to be acquired by the prepared weights. | |||||
言語 | en | |||||
内容記述タイプ | Abstract | |||||
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言語 | en | |||||
出版者 | IEEE | |||||
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言語 | eng | |||||
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資源タイプresource | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
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出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||
DOI | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.1109/CEC.2010.5585950 | |||||
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関連タイプ | isPartOf | |||||
識別子タイプ | ISBN | |||||
関連識別子 | 978-1-4244-6909-3 | |||||
書誌情報 |
en : IEEE Congress on Evolutionary Computation (CEC) p. 1-6, 発行日 2010 |
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値 | author | |||||
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識別子 | http://hdl.handle.net/2237/14440 | |||||
識別子タイプ | HDL | |||||
URI | ||||||
識別子 | http://dx.doi.org/10.1109/CEC.2010.5585950 | |||||
識別子タイプ | DOI |