Analysis of particle interaction in particle swarm optimization

In this paper, we analyze the behavior of particle swarm optimization (PSO) on the facet of particle interaction. We firstly propose a statistical interpretation of particle swarm optimization in order to capture the stochastic behavior of the entire swarm. Based on the statistical interpretation, w...

Full description

Saved in:
Bibliographic Details
Published in:Theoretical computer science 2010-05, Vol.411 (21), p.2101-2115
Main Authors: Chen, Ying-ping, Jiang, Pei
Format: Article
Language:English
Subjects:
Convergence
Particle interaction
Particle swarm optimization
Progress rate
Social-only model
Sphere function
Statistical interpretation
Theoretical analysis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we analyze the behavior of particle swarm optimization (PSO) on the facet of particle interaction. We firstly propose a statistical interpretation of particle swarm optimization in order to capture the stochastic behavior of the entire swarm. Based on the statistical interpretation, we investigate the effect of particle interaction by focusing on the social-only model and derive the upper and lower bounds of the expected particle norm. Accordingly, the lower and upper bounds of the expected progress rate on the sphere function are also obtained. Furthermore, the sufficient and necessary condition for the swarm to converge is derived to demonstrate the PSO convergence caused by the effect of particle interaction.
ISSN:0304-3975
1879-2294
DOI:10.1016/j.tcs.2010.03.003