An Improved Particle Swarm Optimization Algorithm

被引：0
|
作者：
Pan, Dazhi [1 ,2 ]
Liu, Zhibin [2 ]
机构：
[1] China W Normal Univ, Coll Math & Informat, Nanchong 637002, Peoples R China
[2] Southwest Petroleum Univ, Coll Math & Phys, Chengdu 610500, Peoples R China
来源：
EMERGING RESEARCH IN ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE | 2011年 / 237卷
基金：
中国国家自然科学基金;
关键词：
particle swarm optimization; improved particle swarm optimization; sub-optimal location; global optimization; CONVERGENCE;
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：
An improved particle swarm optimization (IPSO) is proposed in this paper. In the new algorithm, the Optimal and sub-optimal locations, which each particle encountered and the swarm meted, are kept. Based on these locations, the IPSO produces four velocities for each particle and obtains the particle's iterative position. The IPSO enlarges the search space and enhances global search ability. From the results obtained through benchmark problems, it is clearly seen that the proposed IPSO method is competitive to the PSO.
引用
收藏
页码：550 / +
页数：2
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