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基于t分布变异的自适应差分进化算法
引用本文:刘兴阳,毛力.基于t分布变异的自适应差分进化算法[J].计算机工程与应用,2012,48(2):127-129.
作者姓名:刘兴阳  毛力
作者单位:江南大学物联网工程学院,轻工过程先进控制教育部重点实验室,江苏无锡214122
基金项目:农业部淡水鱼类遗传育种和养殖生物学重点实验室项目(No.BZ2009-07)
摘    要:为了更好地提高差分进化算法的全局探索和局部开发能力,提出了一种改进的差分进化算法。在该算法中,引入t分布变异算子将高斯变异和柯西变异的优点结合起来,根据以往的进化经验自适应地调整进化策略及交叉概率。通过四个典型的Benchmarks函数的测试结果表明算法具有良好的性能。

关 键 词:差分进化  t分布  进化策略自适应  交叉概率自适应
修稿时间: 

Self-adaptive differential evolution algorithm using mutations based on the t distribution
LIU Xiongyang , MAO Li.Self-adaptive differential evolution algorithm using mutations based on the t distribution[J].Computer Engineering and Applications,2012,48(2):127-129.
Authors:LIU Xiongyang  MAO Li
Affiliation:Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education),School of Internet of Things,Jiangnan University,Wuxi,Jiangsu 214122,China
Abstract:A novel differential evolution algorithm is proposed to improve the exploration and exploitation capabilities of differential evolution(DE).In this algorithm,a new mutation operator following the t distribution is used to integrate the advantages of Gaussian and Cauchy mutation,while both the mutation strategy and crossover probability can be gradually self-adapted by learning from their previous successful experience.Experimental studies are carried out on four classical Benchmark functions,and the computational results show that the algorithm has fast convergence,high accuracy more robustness.
Keywords:differential evolution  t distribution  mutation strategy adaptation  crossover probability adaptation
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