Efficient Real-Coded Genetic Algorithms with Flexible-Step Crossover

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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

  • 電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society  

    電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society 126(5), 654-660, 2006-05-01 

    The Institute of Electrical Engineers of Japan

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各種コード

  • NII論文ID(NAID)
    10018111485
  • NII書誌ID(NCID)
    AN10065950
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    03854221
  • NDL 記事登録ID
    7947325
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-795
  • データ提供元
    CJP書誌  NDL  J-STAGE 
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