Differential evolution based on double populations for constrained multi-objective optimization problem

被引：0
作者：
Meng, Hong-Yun [1 ]
Zhang, Xiao-Hua [2 ]
Liu, San-Yang [1 ]
机构：
[1] Department of Applied Mathematics, Xidian University
[2] Institute of Intelligent Information Processing, Xidian University
来源：
Jisuanji Xuebao/Chinese Journal of Computers | 2008年 / 31卷 / 02期
关键词：
Constrained optimization problem; Differential evolution; Multi-objective optimization problem;
D O I：
10.3724/sp.j.1016.2008.00228
中图分类号：
学科分类号：
摘要：
An improved differential evolution approach is given first, and a new algorithm based on double populations for Constrained Multi-objective Optimization Problem (CMOP) is presented. In the proposed algorithm, two populations are adopted, one is for the feasible solutions found during the evolution, and the other is for infeasible solutions with better performance which are allowed to participate in the evolution with the advantage of avoiding difficulties such as constructing penalty function and deleting infeasible solutions directly. In addition, the time complexity of the proposed algorithm, NSGA-II and SPEA are compared, which show the best is NSGA-II, followed by SPEA and the proposed algorithm simultaneously. The experiments on benchmarks indicate that the proposed algorithm is superior to NSGA-II in the measure of GD and SP.
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收藏
页码：228 / 235
页数：7
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