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- Mutoh Atsuko
- Nagoya Institute of Technology
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- Tanahashi Fumiki
- Toyota Motor Corporation
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- Kato Shohei
- Nagoya Institute of Technology
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- Itoh Hidenori
- Nagoya Institute of Technology
この論文をさがす
抄録
Real-coded genetic algorithms (GAs) are effective methods for function optimization. Generally speaking, the major crossover methods used in real-coded GAs require a large execution time for calculating the fitness of many children at each crossover. Thus, a new crossover method is needed for searching such a large search space efficiently. A novel crossover method that generates children stepwise is proposed and applied to the conventional generation-alternation model. In experiments based on standard test functions and actual problems, the proposed model found an optimal solution 30-40% faster than did the conventional model.
収録刊行物
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- 電気学会論文誌C(電子・情報・システム部門誌)
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電気学会論文誌C(電子・情報・システム部門誌) 126 (5), 654-660, 2006
一般社団法人 電気学会
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詳細情報 詳細情報について
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- CRID
- 1390282679582058496
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- NII論文ID
- 10018111485
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- NII書誌ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL書誌ID
- 7947325
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可