文章基本信息

标题：A Hybrid Genetic Algorithm for Constrained Optimization Problems
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作者：Liu, Da-lian ; Chen, Xiao-hua ; Du, Jin-ling 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2013
卷号：8
期号：2
页码：272-278
DOI：10.4304/jcp.8.2.272-278
语种：English
出版社：Academy Publisher
摘要：Abstract —Genetic algorithm (GA) is a powerful method to solve constrained optimization problems (COPs). In this paper, a new fitness function based hybrid genetic optimization algorithm (NFFHGA) for COPs is proposed, in which a new crossover operator based on Union Design is presented, and inspired by the smooth function technique, a new fitness function is designed to automatically search for potential solutions. Furthermore, in order to make the fitness function work well, a special technique which keeps a certain number of feasible solutions is also used. Experiments on 6 benchmark problems are performed and the compared results with the best known solutions reported in literature show that NFFHGA can not only quickly converge to the optimal or near-optimal solutions, but also have a high performance.
关键词：Constrained optimization;genetic algorithm;fitness function;Uniform Design.