文献类型：会议论文

英文题名：Chaos-genetic algorithm for multiobjective optimization

作者：Qi, Rongbin[1];Qian, Feng[1];Li, Shaojun[1];Wang, Zhenlei[1]

机构：[1]East China Univ Sci & Technol, Automat Inst, Shanghai 200237, Peoples R China

会议论文集：6th World Congress on Intelligent Control and Automation

会议日期：JUN 21-23, 2006

会议地点：Dalian, PEOPLES R CHINA

语种：英文

外文关键词：multiobjective optimisation; chaos; genetic algorithm; nondominated sorting

摘要：Chaos-genetic algorithm (CGA) combining local chaotic search and nondominated sorting genetic algorithm for multiobjective optimization is proposed. The method is composed of two stages. The wide search with nondominated sorting genetic algorithm (NSGA-II) is performed at the first searching stage, then the local search with chaotic mutation is performed at the second stage. Moreover, we cancel the limitation of the number of the elitism at each generation and improve the original clustering method. We apply the coverage measure and spread measure to evaluate the performance of the two methods, and obtain more satisfactory results with CGA than that with NSGA-II.