A modified adaptive particle swarm optimization algorithm

被引：0
|
作者：
Lei, Wang [1 ]
Qi, Kang [1 ]
Hui, Xiao [1 ]
Wu Qidi [1 ]
机构：
[1] Tongji Univ, Control Dept, Shanghai 200092, Peoples R China
来源：
2005 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY - (ICIT), VOLS 1 AND 2 | 2005年
关键词：
particle swarm optimization; multi-optimum; fuzzy programming;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
It is effective to avoid failing into local optimums at the original stage of the computation that the knowledge of multi-optimum distribution state is introduced into general programming of the particle swarm movement in particle swarm optimization. But if the proportion factor of multi-optimum programming cannot be dynamic adjusted in the optimization process, the performance of the algorithm will be limited. In this paper, a modified adaptive particle swarm optimization algorithm based on fuzzy and adaptive programming of multi-optimum was put forward and simulated. In the modified algorithm derived in this paper, proportion factor of multi-optimum programming can be dynamic adjusted in the optimization process, and simulation results show that it has well general convergence character.
引用
收藏
页码：273 / 278
页数：6
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