The optimization of genetic algorithm control parameters

Minle Wang, Xiaoguang Gao

科研成果: 会议稿件论文同行评审

1 引用 (Scopus)

摘要

In this paper, the new methods of optimizing Genetic Algorithm control parameters are presented, including the method of adjusting crossover probability and mutation probability, the dynamic convergence rule and the method of determining the optimal population size. All the methods can be applied to enhancing Genetic Algorithm running efficiency and preventing premature convergence.

源语言英语
2504-2507
页数4
出版状态已出版 - 2002
活动Proceedings of the 4th World Congress on Intelligent Control and Automation - Shanghai, 中国
期限: 10 6月 200214 6月 2002

会议

会议Proceedings of the 4th World Congress on Intelligent Control and Automation
国家/地区中国
Shanghai
时期10/06/0214/06/02

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