Genetic Algorithm with Evolutionary Chain-Based Mutation and Its Applications

• Ye Ju

• Tanaka Masahiro

• Tanino Tetsuzo

抄録

Mutation is one of the important operators in genetic algorithm. In traditional genetic algorithm, mutation is activated stochastically. In this way it is unknown and cannot be controlled for which individuals to be mutated. Therefore, it is unavoidable that some good individuals are destroyed by mutation and then the evolutionary efficiency of the genetic algorithm is dampened. Owing to this kind of destructivity of mutation, the operator of mutation has to be limited within a very small probability, and the potentiality of mutation is consequently limited. In this paper, we present an evolutionary chain-based mutation and a control strategy of reasonable competition, in which the heuristic information provided by the evaluation function is well utilized. This method avoids the blindness of stochastic mutation. The performance improved in this method is shown by two examples, a fuzzy modeling for the identification of a nonlinear function and a typical combinatorial optimization problem-the traveling salesman problem.

収録刊行物

• Memoirs of the Faculty of Engineering, Okayama University

  Memoirs of the Faculty of Engineering, Okayama University 30 (1), 111-120, 1995-12-28

  Faculty of Engineering, Okayama University

詳細情報

• CRID: 1390009224548532736
• NII論文ID: 120002307635
• NII書誌ID: AA10699856
• ISSN: 04750071
• DOI: 10.18926/15386
• Web Site: https://ousar.lib.okayama-u.ac.jp/15386
• 本文言語コード: en
• データソース種別:
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  • IRDB
  • CiNii Articles