The limited mutation particle swarm optimizer

被引:0
|
作者
Song, Chunhe [1 ]
Zhao, Hai [1 ]
Cai, Wei [1 ]
Zhang, Haohua [1 ]
Zhao, Ming [1 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110006, Peoples R China
来源
BIO-INSPIRED COMPUTATIONAL INTELLIGENCE AND APPLICATIONS | 2007年 / 4688卷
关键词
D O I
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
Similar with other swarm algorithms, the PSO algorithm also suffers from premature convergence. Mutation is a widely used strategy in the PSO algorithm to overcome the premature convergence. This paper discusses some induction patterns of mutation (IPM) and typical algorithms, and then presents a new PSO algorithm - the Limited Mutation PSO algorithm. Basing on a special PSO model depicted as "social-only", the LMPSO adopts a new mutation strategy - limited mutation. When the distance between one particle and the global best location is less than a threshold predefined, some dimensions of the particles will mutate under specific rules. The LMPSO is compared to other five different types of PSO with mutation strategy, and the experiment results show that the new algorithm performances better on a four-function test suite with different dimensions.
引用
收藏
页码:258 / 266
页数:9
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