Adaptive Particle Swarm Optimization with Dynamic Population and Its Application to Constrained Engineering Design Optimization

被引：0

作者：

Liu, Yi ^{[1
]}

Mu, Caihong ^{[1
]}

Kou, Weidong ^{[2
]}

Liu, Jing ^{[3
]}

机构：

[1] Xidian Univ, Sch Elect Engn, Xian, Peoples R China

[2] IBM Corp, Beijing, Peoples R China

[3] Xian Univ Posts & Telecommun, Sch Elect Engn, Xian, Peoples R China

来源：

MATERIALS PROCESSING TECHNOLOGY II, PTS 1-4 | 2012年 / 538-541卷

基金：

中国国家自然科学基金;

关键词：

Evolutionary computation; Constrained engineering design optimization; Particle swarm optimization (PSO); ALGORITHM;

D O I：

10.4028/www.scientific.net/AMR.538-541.3074

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper presents a variant of the particle swarm optimization (P SO) that we call the adaptive particle swarm optimization with dynamic population (DP-APSO), which adopts a novel dynamic population (DP) strategy whereby the population size of swarm can vary with the evolutionary process. The DP strategy enables the population size to increase when the swarm converges and decrease when the swarm disperses. Experiments were conducted on two well-studied constrained engineering design optimization problems. The results demonstrate better performance of the DP-APSO in solving these engineering design optimization problems when compared with two other evolutionary computation algorithms.

引用

页码：3074 / +

页数：2

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