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一种改进的多目标演化算法
引用本文:龚正,王毅,周佳.一种改进的多目标演化算法[J].计算机工程与应用,2010,46(26):43-45.
作者姓名:龚正  王毅  周佳
作者单位:湘潭大学,信息工程学院,湖南,湘潭,411105
摘    要:保持解集的多样性和分布性是多目标进化算法的关键之一。在NSGA-II的基础上,提出了一种用混合距离来估计个体的拥挤度,并使用优先队列根据个体的混合距离来逐个删除种群中超出的非劣解以保持解的多样性,实验结果表明,HD-NSGA-II比NSGA-II的解分布的更加合理且分布度有很大的提高。

关 键 词:多目标进化算法  混合距离  优先队列  多样性
收稿时间:2009-3-5
修稿时间:2009-5-25  

Improved multi-objective evolutionary algorithm
GONG Zheng,WANG Yi,ZHOU Jia.Improved multi-objective evolutionary algorithm[J].Computer Engineering and Applications,2010,46(26):43-45.
Authors:GONG Zheng  WANG Yi  ZHOU Jia
Affiliation:(Institute of Information Engineering, Xiangtan Universtity, Xiangtan, Hunan 411105, China)
Abstract:Preserving the diversity of solution is a key for multi-objective evolution algorithm.This paper improves of NS- GA-Ⅱ, it suggests a new approach to measure individual crowding distance by hybrid distance and uses priority queue to prune the over-plus of non-dominated solution one by one according hybrid distance for preserving the diversity of solution. Experimental results show that the HD-NSGA-Ⅱ can obtain reasonable distributing solution and diversity of this algorithm are more efficient than NSGA-Ⅱ.
Keywords:multi-objective evolution algorithm  hybrid distance  priority queue  diversity
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