Improved Particle Swarm Optimization Based on Genetic Algorithm

被引：0
|
作者：
Dou, Chunhong [1 ]
Lin, Jinshan [1 ]
机构：
[1] Weifang Univ, Sch Informat & Control Engn, Weifang 261061, Peoples R China
来源：
SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING: THEORY AND PRACTICE, VOL 2 | 2012年 / 115卷
关键词：
Particle swarm optimization (PSO); improved particle swarm optimization (IPSO); genetic algorithm (GA);
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：
The particle swarm optimization (PSO) algorithm is an intelligent optimization algorithm and has been successfully applied to many fields. However, it has the deficiencies of the poor search capability and the low calculation efficiency. To solve the problems, the genetic algorithm is introduced to improve the PSO algorithm in the paper. Then, three simulated examples were used to assess the ability of the improved PSO algorithm. The results showed that the improved PSO algorithm could jump out of the local minimum and achieve the better solution. Furthermore, the paper reveals that the improved PSO algorithm seems to be an improvement on the original PSO algorithm.
引用
收藏
页码：149 / 153
页数：5
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