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

Yi Liu; Cai Hong Mu; Wei Dong Kou; Jing Liu

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

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 538-541Adaptive Particle Swarm Optimization with Dynamic...

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

Abstract:

This paper presents a variant of the particle swarm optimization (PSO) 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.

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Periodical:

Advanced Materials Research (Volumes 538-541)

Pages:

3074-3078

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.538-541.3074

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Online since:

June 2012

Authors:

Yi Liu, Cai Hong Mu, Wei Dong Kou, Jing Liu

Keywords:

Constrained Engineering Design Optimization, Evolutionary Computation, Particle Swarm Optimization (PSO)

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