Multi-population cooperative particle swarm optimization

被引:0
|
作者
Niu, B [1 ]
Zhu, YL
He, XX
机构
[1] Chinese Acad Sci, Shenyang Inst Automat, Shenyang 110016, Peoples R China
[2] Chinese Acad Sci, Grad Sch, Beijing 100039, Peoples R China
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暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Inspired by the phenomenon of symbiosis in natural ecosystem, a master-slave mode is incorporated into Particle Swarm Optimization (PSO), and a Multi-population Cooperative Optimization (MCPSO) is thus presented. In MCPSO, the population consists of one master swarm and several slave swarms. The slave swarms execute PSO (or its variants) independently to maintain the diversity of particles, while the master swarm enhances its particles based on its own knowledge and also the knowledge of the particles in the slave swarms. In the simulation part, several benchmark functions are performed, and the performance of the proposed algorithm is compared to the standard PSO (SPSO) to demonstrate its efficiency.
引用
收藏
页码:874 / 883
页数:10
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