Optimal parameter regions and the time-dependence of control parameter values for the particle swarm optimization algorithm

dc.contributor.authorHarrison, Kyle Robert
dc.contributor.authorEngelbrecht, Andries P.
dc.contributor.authorOmbuki-Berman, Beatrice M.
dc.contributor.emailengel@cs.up.ac.zaen_ZA
dc.date.accessioned2018-02-06T05:04:40Z
dc.date.issued2018-08
dc.description.abstractThe particle swarm optimization (PSO) algorithm is a stochastic search technique based on the social dynamics of a flock of birds. It has been established that the performance of the PSO algorithm is sensitive to the values assigned to its control parameters. Many studies have examined the long-term behaviours of various PSO parameter configurations, but have failed to provide a quantitative analysis across a variety of benchmark problems. Furthermore, two important questions have remained unanswered. Specifically, the effects of the balance between the values of the acceleration coefficients on the optimal parameter regions, and whether the optimal parameters to employ are time-dependent, warrant further investigation. This study addresses both questions by examining the performance of a global-best PSO using 3036 different parameter configurations on a set of 22 benchmark problems. Results indicate that the balance between the acceleration coefficients does impact the regions of parameter space that lead to optimal performance. Additionally, this study provides concrete evidence that, for the examined problem dimensions, larger acceleration coefficients are preferred as the search progresses, thereby indicating that the optimal parameters are, in fact, time-dependent. Finally, this study provides a general recommendation for the selection of PSO control parameter values.en_ZA
dc.description.departmentComputer Scienceen_ZA
dc.description.embargo2019-08-01
dc.description.librarianhj2018en_ZA
dc.description.sponsorshipThe National Research Foundation (NRF) of South Africa (Grant Number 46712) and the Natural Sciences and Engineering Research Council of Canada (NSERC).en_ZA
dc.description.urihttp://www.elsevier.com/locate/swevoen_ZA
dc.identifier.citationK.R. Harrison, et al., Optimal parameter regions and the time-dependence of control parameter values for the particle swarm optimization algorithm, Swarm and Evolutionary Computation (2018) 41:20-35, https://doi.org/10.1016/j.swevo.2018.01.006.en_ZA
dc.identifier.issn2210-6502
dc.identifier.other10.1016/j.swevo.2018.01.006
dc.identifier.urihttp://hdl.handle.net/2263/63858
dc.language.isoenen_ZA
dc.publisherElsevieren_ZA
dc.rights© 2018 Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Swarm and Evolutionary Computation. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Swarm and Evolutionary Computation, vol. 41, pp. 20-35, 2018. doi : 10.1016/j.swevo.2018.01.006.en_ZA
dc.subjectParticle swarm optimization (PSO)en_ZA
dc.subjectControl parameter valuesen_ZA
dc.subjectTime-dependenceen_ZA
dc.subjectStochastic search techniquesen_ZA
dc.subjectOptimal performanceen_ZA
dc.subjectLong term behavioursen_ZA
dc.subjectBench-mark problemsen_ZA
dc.subjectAcceleration coefficientsen_ZA
dc.subjectStochastic systemsen_ZA
dc.subjectParameter estimationen_ZA
dc.subjectOptimizationen_ZA
dc.subjectBenchmarkingen_ZA
dc.titleOptimal parameter regions and the time-dependence of control parameter values for the particle swarm optimization algorithmen_ZA
dc.typePostprint Articleen_ZA

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