The Analysis of Continuous Particle Swarm Optimization Algorithm's Mean Square Convergence

doi:10.3969/j.issn.0372-2112.2012.07.013

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ACTA ELECTRONICA SINICA ›› 2012, Vol. 40 ›› Issue (7) : 1364-1367. DOI: 10.3969/j.issn.0372-2112.2012.07.013

The Analysis of Continuous Particle Swarm Optimization Algorithm's Mean Square Convergence

LUO Jin-yan

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Abstract

Particle swarm optimization (PSO) algorithm is a population-based,self-adaptive search optimization method motivated by the observation of simplified animal social behaviors.Most of the analysis of PSO algorithm is in the deterministic assumptions.Based on the theory of stochastic process,this paper studies the mean square convergence of the particle swarm optimization algorithm.Simulations demonstrate the validity of the proposed method.

Key words

moment equations / stochastic process / particle swarm optimization / mean square convergence

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LUO Jin-yan. The Analysis of Continuous Particle Swarm Optimization Algorithm's Mean Square Convergence[J]. Acta Electronica Sinica, 2012, 40(7): 1364-1367. https://doi.org/10.3969/j.issn.0372-2112.2012.07.013

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Funding

National Natural Science Foundation of Fujian Province, China (No.2009J05011); Science and Technology Research Program of Minjiang University (No.YKQ09001)