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

页码：273 / 278

页数：6

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