Study on Improving the Fitness Value of Multi-objective Evolutionary Algorithms

摘要：

Pareto sort classification method is often used to compute the fitness value of evolutionary groups in multi-objective evolutionary algorithms.However this kind of computation may produce great selection pressure and result in premature convergence. To address this problem,an improved method to compute the fitness value of multi-objective evolutionary algorithms based on the relative relationship between objective function values is proposed in this paper, which improves the convergence and distribution of multi-objective evolutionary algorithms. Testing results of test functions show that the improved computation method has a higher ability of convergence and distribution than the evolutionary algorithm based on Pareto sort classification method.

关键词： multi-objective evolutionary algorithm improved fitness value computation method

作者: YongGang Wu Gu Wei

作者单位: College of hydroelectricity and digitalization Eng.HUST.WuH_an.China

会议类型: 国际会议

会议名称: The Ninth International Workshop on Meta-Synthesis Complez Systems(第九届综合集成与复杂国际研讨会)

会议地点: 成都

会议语种:英文

页码: 129-136

在线出版日期: 2009-06-21（万方平台首次上网日期，不代表论文的发表时间）