Particle swarm optimization with a new update mechanism

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dc.contributor.authorKiran, Mustafa Servet
dc.date.accessioned2020-03-26T19:42:16Z
dc.date.available2020-03-26T19:42:16Z
dc.date.issued2017
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractParticle swarm optimization (PSO) has been invented by inspiring social behaviors of fish or birds to solve nonlinear global optimization problems. Since its invention, many PSO variants have been proposed by modifying its solution update rule to improve its performance. The social component of update rule of PSO is based on subtraction between current position of particle and global best information. Similarly, the cognitive component works by using subtraction between the current position of particle and personal best information. The subtraction-based solution update mechanism has caused premature convergence and stagnation in particle population during the iterations. To overcome these issues, this study presents a distribution-based update rule for PSO algorithm. The performance of proposed approach named as PSOd is investigated on solving 13 nonlinear global optimization benchmark functions and three constrained engineering optimization problems. Obtained results are compared with standard PSO algorithm, its classical variants and some state-of-art swarm intelligence algorithms. The experimental results and comparisons show that PSOd outperforms PSO and its variants on solving the numerical benchmark functions in terms of solution quality and robustness. (C) 2017 Elsevier B.V. All rights reserved.en_US
dc.identifier.doi10.1016/j.asoc.2017.07.050en_US
dc.identifier.endpage678en_US
dc.identifier.issn1568-4946en_US
dc.identifier.issn1872-9681en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage670en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.asoc.2017.07.050
dc.identifier.urihttps://hdl.handle.net/20.500.12395/35365
dc.identifier.volume60en_US
dc.identifier.wosWOS:000414072200049en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherELSEVIER SCIENCE BVen_US
dc.relation.ispartofAPPLIED SOFT COMPUTINGen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectParticle swarm optimizationen_US
dc.subjectGlobal optimizationen_US
dc.subjectDistribution-based updateen_US
dc.titleParticle swarm optimization with a new update mechanismen_US
dc.typeArticleen_US

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