A modified strategy for the constriction factor in particle swarm optimization

被引：0

作者：

Bui, Lam T. ^{[1
]}

Soliman, Omar ^{[1
]}

Abbass, Hussein A. ^{[1
]}

机构：

[1] Univ New S Wales, UNSW ADFA, Sch ITEE, Artificial Life & Adapt Robot Lab, Canberra, ACT, Australia

来源：

PROGRESS IN ARTIFICIAL LIFE, PROCEEDINGS | 2007年 / 4828卷

关键词：

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：

In this paper, we propose a modification to particle swarm optimization in order to speed up the optimization process. The modification is applied to the constriction coefficient, an important parameter that controls the convergence rate. To validate the proposed strategy, we carried out a number of experiments on a wide range of 25 standard test problems. The obtained results show that the proposed strategy significantly improves the performance of the selected PSO algorithm.

引用

页码：333 / 344

页数：12

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