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提高MOEAs解集的分布性——一种基于∞范数的逐步方法 被引量：1

Increase diversity of solutions of MOEAs——∞-norm based stepwise method
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摘要 解集的分布性是多目标优化中最重要的研究工作之一,解集的分布性主要体现在两个方面,一是解集的分布广度;二是解集的均匀性。在多目标进化算法(MOEAs)中,解集分布性的保持放在种群维护中实现,提出一种基于∞范数的逐步方法(INS)来提高MOEAs解集的分布性,INS用∞范数来衡量个体的分布性,用逐步的方法来裁剪个体。通过与目前最流行的两个MOEAs——NSGA-II和ε-MOEA,在9个测试函数上进行实验,结果表明INS能很好地提高解集的分布性。 Diversity of solutions is one of the most important jobs of multi-objective optimization.Diversity includes the span and uniformity.In Multi-Objective Evolutionary Algorithms（MOEAs）,population maintenance is used to realize the diversity.In this paper,a ∞-norm（infinite norm） based stepwise（INS） method is proposed to increase diversity of MOEAs.INS use ∞-norm as a measurement of diversity of individuals,and use stepwise method to wipe off individuals form population.Through experiments on 9 test problems,compared with two most popular MOEAs——NSGA-Ⅱ and ε-MOEA,the experimental results demonstrate that INS can increase diversity of solutions obviously.
作者 曾映兰 郑金华 罗彪
机构地区 湘潭大学信息工程学院
出处 《计算机工程与应用》 CSCD 北大核心 2009年第10期49-53,共5页 Computer Engineering and Applications
基金 国家自然科学基金No.60773047 湖南省教育厅重点科研项目(No.06A074) 湘潭大学校级科研项目(No.06XZX06)~~
关键词 多目标进化算法 种群维护 分布性 ∞范数 逐步 multi-objective evolutionary algorithms population maintenance diversity ∞-norm stepwise
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
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参考文献18

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同被引文献15

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2009年 第10期

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