変数間の依存関係の有無に着目した実数値GAの提案とその性能評価  [in Japanese] A Real-Coded Genetic Algorithm Taking Account of Epistasis among Parameters and Its Performance Evaluation  [in Japanese]

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Author(s)

Abstract

The Genetic algorithm (GA) is a powerful optimization framework inspired by the evolution process of natural life. GAs for function optimization can be categorized into two groups : bit-string GAs and real-coded GAs. UNDX+MGG is a real-coded GA that has shown good performance on multi-modal functions with epistasis among parameters, which are difficult to solve for conventional methods. However, the conventional UNDX+MGG has a problem from a viewpoint of search efficiency because the conventional UNDX+MGG always assumes epistasis among the all parameters and searches the all parameters at the same time. In this paper, we propose a new method for making the search effective by estimating epistasis among parameters and reducing the number of parameters to be simultaneously searched.

Journal

  • インテリジェント・システム・シンポジウム講演論文集 = FAN Symposium : fuzzy, artificial intelligence, neural networks and computational intelligence

    インテリジェント・システム・シンポジウム講演論文集 = FAN Symposium : fuzzy, artificial intelligence, neural networks and computational intelligence 12, 415-420, 2002-11-14

    日本機械学会

References:  13

Codes

  • NII Article ID (NAID)
    110002496754
  • NII NACSIS-CAT ID (NCID)
    AA1190206X
  • Text Lang
    JPN
  • Article Type
    SHO
  • Data Source
    CJP  NII-ELS  NDL-Digital 
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