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Mean and variance of the sampling distribution of particle swarm optimizers during stagnation

Poli, R (2009) 'Mean and variance of the sampling distribution of particle swarm optimizers during stagnation.' IEEE Transactions on Evolutionary Computation, 13 (4). 712 - 721. ISSN 1089-778X

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Abstract

Several theoretical analyses of the dynamics of particle swarms have been offered in the literature over the last decade. Virtually all rely on substantial simplifications, often including the assumption that the particles are deterministic. This has prevented the exact characterization of the sampling distribution of the particle swarm optimizer (PSO). In this paper we introduce a novel method that allows us to exactly determine all the characteristics of a PSO sampling distribution and explain how it changes over any number of generations, in the presence stochasticity. The only assumption we make is stagnation, i.e., we study the sampling distribution produced by particles in search for a better personal best. We apply the analysis to the PSO with inertia weight, but the analysis is also valid for the PSO with constriction and other forms of PSO. © 2009 IEEE.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 05 Mar 2013 14:13
Last Modified: 23 Jan 2019 06:15
URI: http://repository.essex.ac.uk/id/eprint/5551

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