电子学报 ›› 2010, Vol. 38 ›› Issue (9): 2090-2094.

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噪声环境下遗传算法的性能评价

黎 明, 李军华   

  1. 南昌航空大学无损检测教育部重点实验室,江西南昌 330063
  • 收稿日期:2009-08-12 修回日期:2010-02-10 出版日期:2010-09-25 发布日期:2010-09-25

Performance Evaluation of Genetic Algorithm in Noisy Environments

LI Ming, LI Jun-hua   

  1. Key Laboratory of Nondestructive Testing (Ministry of Education) of Nanchang Hang Kong University,Nanchang,Jiangxi 330063,China
  • Received:2009-08-12 Revised:2010-02-10 Online:2010-09-25 Published:2010-09-25

摘要: 为了评价遗传算法在噪声环境下的优化性能,提出"平均最优解"和"最优解分布标准差"两个指标,实验结果表明新指标可以有效地评价噪声环境下遗传算法的优化性能.研究了实数编码遗传算法在噪声强度递增环境下的性能.结果表明小生境策略和多种群策略可以改善遗传算法在噪声环境下的性能,单点交叉在噪声环境下的性能要优于混合交叉.

关键词: 遗传算法, 噪声环境, 性能评价

Abstract: "The average of best" and "the standard deviation of best" were proposed to evaluate the performance of genetic algorithms in noisy environment.Results show the evaluation indexes could effectively evaluate the performance of genetic algorithm in the environment.Based on this,the performances of real-coded genetic algorithms with different crossover operator in noisy environment have been investigated.Results show the performance of deterministic crowding genetic algorithm and multi population genetic algorithm in the environment are better than that of elist genetic algorithm;the behaviors of alone point crossover outperform that of blended crossover.

Key words: genetic algorithm, noisy environment, performance evaluation

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