Particle Swarm Optimization Based on Clustering in Searching Process

被引：0
|
作者：
He, Dakuo [1 ]
Meng, Yi [1 ]
Zhang, Erwei [1 ]
Wang, Guanyu [1 ]
机构：
[1] Northeastern Univ, Sch Informat Sci & Engn, Shenyang, Peoples R China
来源：
PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2012年
关键词：
particle swarm optimization; the population distribution; clustering; fitness value; normalization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The population distribution of Particle Swarm Optimization (PSO) directly concerns global convergence and searching efficiency of PSO. The reasonable setting of population distribution and operational parameters is an important problems in the application of PSO to perform optimization calculation. Based on the study on how to set the population distribution, such conclusion can be drawn that the population distribution must reflect the information on solution space scientifically. The PSO based on the population distribution of clustering is proposed. The population distribution was analyzed according to the discrepancy in the solution space and objective function space. The integrated clustering index, which combines the fitness value and space location, was applied to design the population distribution. Simulation results show that the method is feasible and effective.
引用
收藏
页码：2884 / 2887
页数：4
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