Increasing Robustness of Binary-coded Genetic Algorithm

• Mao Jiangming

  Graduate School of Information Science and Electrical Eng., Kyushu University

• Hirasawa Kotaro

  Graduate School of Information, Production and Systems, Waseda University

• Hu Jinglu

  Graduate School of Information, Production and Systems, Waseda University

• Murata Junichi

  Graduate School of Information Science and Electrical Eng., Kyushu University

抄録

Genetic algorithms are often well suited for optimization problems because of their parallel searching and evolutionary ability. Crossover and mutation are believed to be the main exploration operators. In this paper, we focus on how crossover and mutation work in binary-coded genetic algorithm and investigate their effects on bit’s frequency of population. According to the analysis of equilibrium of crossover, we can see the bit-based simulated crossover (BSC) is strong crossover method. Furthermore, to increase robustness of binary-coded genetic algorithm, multi-generation inheritance evolutionary strategy(MGIS) was proposed. Simulation results demonstrate the effectiveness of the proposed method.

収録刊行物

• 電気学会論文誌Ｃ（電子・情報・システム部門誌）

  電気学会論文誌Ｃ（電子・情報・システム部門誌） 123 (9), 1625-1630, 2003

  一般社団法人 電気学会

キーワード

• Binary Genetic Algorithm
• Robustness of GA
• Bit Simulated Crossover
• Equilibrium of crossover
• Multi-generation Inheritance Evolutionary Strategy

詳細情報

• CRID: 1390001204606267136
• NII論文ID: 10011751090
• NII書誌ID: AN10065950
• DOI: 10.1541/ieejeiss.123.1625
• ISSN: 13488155
• ISSN: 03854221
• NDL書誌ID: 6692718
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I6692718
• Web Site: http://www.jstage.jst.go.jp/article/ieejeiss/123/9/123_9_1625/_pdf
• 本文言語コード: en
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