An Extended ISM for Globally Multimodal Function Optimization by Genetic Algorithms
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
284-289 頁
2009-11 発行
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この文献の参照には次のURLをご利用ください : https://ir.lib.hiroshima-u.ac.jp/00028458
| ファイル情報(添付) | |
| タイトル ( eng ) |
An Extended ISM for Globally Multimodal Function Optimization by Genetic Algorithms
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| 作成者 |
Karatsu Naoya
Nagata Yuichi
Ono Isao
Kobayashi Shigenobu
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| 収録物名 |
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
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| 開始ページ | 284 |
| 終了ページ | 289 |
| 抄録 |
When attempting to optimize a function where exists several big-valley structures, conventional GAs often fail to find the global optimum. Innately Split Model (ISM) is a framework of GAs, which is designed to avoid this phenomenon called UV -Phenomenon. However, ISM doesn't care about previouslysearched areas by the past populations. Thus, it is possible that populations of ISM waste evaluation cost for redundant searches reaching previously-found optima. In this paper, we introduce Extended ISM (EISM) that uses search information of past populations as trap to suppress overlapping searches. To show performance of EISM, we apply it to some test functions, and analyze the behavior.
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| NDC分類 |
技術・工学 [ 500 ]
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| 言語 |
英語
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| 資源タイプ | 会議発表論文 |
| 出版者 |
IEEE SMC Hiroshima Chapter
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| 発行日 | 2009-11 |
| 権利情報 |
(c) Copyright by IEEE SMC Hiroshima Chapter.
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| 出版タイプ | Version of Record（出版社版。早期公開を含む） |
| アクセス権 | オープンアクセス |
| 収録物識別子 |
[ISSN] 1883-3977
[URI] http://www.hil.hiroshima-u.ac.jp/iwcia/2009/
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