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Multi-objective Particle Swarm Optimization considering the diversity of the inferior solutions
https://doi.org/10.24517/00007841
https://doi.org/10.24517/00007841fefc0eba-f318-4d37-83cc-f0092a6ab438
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
TE-PR-KITAYAMA-T-1575.pdf (484.0 kB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||||||||
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| 公開日 | 2017-10-03 | |||||||||||
| タイトル | ||||||||||||
| タイトル | Multi-objective Particle Swarm Optimization considering the diversity of the inferior solutions | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||
| 資源タイプ | journal article | |||||||||||
| ID登録 | ||||||||||||
| ID登録 | 10.24517/00007841 | |||||||||||
| ID登録タイプ | JaLC | |||||||||||
| その他のタイトル | ||||||||||||
| 値 | 非劣解の多様性を考慮した多目的 Particle Swarm Optimization | |||||||||||
| 著者 |
Kitayama, Satoshi
× Kitayama, Satoshi× Arakawa, Masao× Yamazaki, Koetsu |
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| 著者別表示 |
北山, 哲士
× 北山, 哲士
× 荒川, 雅生
× 山崎, 光悦
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| 書誌情報 |
Nihon Kikai Gakkai Ronbunshu, C Hen / Transactions of the Japan Society of Mechanical Engineers, Part C 巻 74, 号 742, p. 1575-1583, 発行日 2008-06-01 |
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| ISSN | ||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||
| 収録物識別子 | 0387-5024 | |||||||||||
| NCID | ||||||||||||
| 収録物識別子タイプ | NCID | |||||||||||
| 収録物識別子 | AN00187463 | |||||||||||
| DOI | ||||||||||||
| 関連タイプ | isIdenticalTo | |||||||||||
| 識別子タイプ | DOI | |||||||||||
| 関連識別子 | https://doi.org/10.1299/kikaic.74.1575 | |||||||||||
| 出版者 | ||||||||||||
| 出版者 | 日本機械学会 | |||||||||||
| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | In this paper, a simple method for the multi-objective optimization problems by the Particle Swarm Optimization (PSO) is proposed. The objectives of the Multi Objective Evolutionary Algorithms (MOEA) are summarized as follows : (1) To find the pareto optimal solutions, (2) To find the pareto optimal solutions as diverse as possible. To achieve these objectives by the PSO for the single objective problems, we propose how to define the g-best in this swarm without introducing some new parameters. That is, one particle among the non-inferior solutions is selected as the g-best to achieve the diversity among the non inferior solutions. The relative distance in the objective space is utilized to select the gbest among the non-inferior solutions. Additionally, some particles among the non inferior solutions are also selected as the gbest of the inferior solutions to find the pareto optimal solutions. The absolute distance in the objective space is utilized to select the g-best of the inferior solutions. We also show the geometric interpretation about the movement of particles. The validity of proposed approach is examined through typical numerical examples. | |||||||||||
| 著者版フラグ | ||||||||||||
| 出版タイプ | VoR | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||
