Multiple Swarms Multi-objective Particle Swarm Optimization Based on Decomposition

被引:5
|
作者
Peng Hu [1 ]
Li Rong [1 ]
Cao Liang-lin [1 ]
Li Li-xian [1 ]
机构
[1] Jiujiang Univ, Sch Informat Sci & Technol, Jiujiang 332005, Peoples R China
来源
CEIS 2011 | 2011年 / 15卷
关键词
Multi-objective particle swarm optimization; Multi-swarm particle swarm optimization; Multi-objective decomposition; Performance indicator;
D O I
10.1016/j.proeng.2011.08.632
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Particle swarm optimization is a very competitive swarm intelligence algorithm for multi-objective optimization problems, but because of it is easy to fall into local optimum solution, and the convergence and accuracy of Pareto solution set is not satisfactory. So we proposed a multi-swarm multi-objective particle swarm optimization based on decomposition (MOPSO_MS), in the algorithm each sub-swarm corresponding to a sub-problem which decomposed by multi-objective decomposition method, and we constructed a new updates strategy for the velocity. Finally, through simulation experiments and compare with the state-of-the-art multi-objective particle swarm algorithm on ZDT test function proved the convergence and the accuracy of the algorithm. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]
引用
收藏
页数:5
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