文献类型：期刊文献

中文题名：基于精英选择和个体迁移的多目标遗传算法

英文题名：Multiobjective genetic algorithm based on elitist selection and individual migration

作者：祁荣宾[1];钱锋[1];杜文莉[1];颜学峰[1]

机构：[1]华东理工大学自动化研究所,上海200237

年份：2007

卷号：22

期号：2

起止页码：164

中文期刊名：控制与决策

外文期刊名：Control and Decision

收录：CSTPCD;;EI(收录号：20071610558037);Scopus;北大核心:【北大核心2004】；CSCD:【CSCD2011_2012】；

基金：国家973计划项目(2002CB3122000);国家863计划项目(2003AA412010;AA413130);2006上海市博士后科研基金项目

语种：中文

中文关键词：多目标优化;遗传算法;Pareto最优解

外文关键词：Multiobjective optimization;Genetic algorithm;Pareto optimal solutions

摘要：提出基于遗传算法求解多目标优化问题的方法,将多目标问题分解成多个单目标优化问题,用遗传算法分别在每个单目标种群中并行搜索.在进化过程中的每一代,采用精英选择和个体迁移策略加快多个目标的并行搜索,提出了控制Pareto最优解数量并保持个体多样性的有限精度法,同时还提出了多目标遗传算法的终止条件.数值实验说明所提出的算法能较快地找到一组分布广泛且均匀的Pareto最优解.
A new method is proposed to solve multiobjective optimization based on genetic algorithm.The method is implemented to optimize each one of the multiobjective problem separately by parallel searching of genetic algorithm.At each generation of the evolving process,an elitist selection and individual migration to improve the parallel searching speed is applied.Finite precision method is applied to control the amount of the Pareto optimal solutions and keep the individual diversity.At the same time,a new stopping condition of multiobjective genetic algorithm is proposed.The numerical results demonstrate that the proposed method can fleetly find the Pareto optimal solutions which formerly are scattered extensively and uniformly.