Particle swarm with equilibrium strategy of selection for multi-objective optimization

被引：25
|
作者：
Wang, Yujia [1 ]
Yang, Yupu [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
来源：
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH | 2010年 / 200卷 / 01期
关键词：
Particle swarm; Equilibrium strategy of selection; Multi-objective optimization; Preference ordering; EVOLUTIONARY ALGORITHM;
D O I：
10.1016/j.ejor.2008.12.026
中图分类号：
C93 [管理学];
学科分类号：
12 ; 1201 ; 1202 ; 120202 ;
摘要：
A new ranking scheme based on equilibrium strategy of selection is proposed for multi-objective particle swarm optimization (MOPSC), and the preference ordering is used to identify the "best compromise" in the ranking stage. This scheme increases the selective pressure, especially when the number of objectives is very large. The proposed algorithm has been compared with other multi-objective evolutionary algorithms (MOEAs). The experimental results indicate that our algorithm produces better convergence performance. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码：187 / 197
页数：11
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