Particle Swarm Optimization from Theory to Applications

Int. J. Rough Sets Data Anal. Pub Date : 2018-04-01 DOI:10.4018/IJRSDA.2018040101

M. El-Shorbagy, A. Hassanien

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引用次数: 65

Abstract

Particle swarm optimization (PSO) is considered one of the most important methods in swarm intelligence.PSOisrelatedtothestudyofswarms;whereitisasimulationofbirdflocks.Itcanbe usedtosolveawidevarietyofoptimizationproblemssuchasunconstrainedoptimizationproblems, constrainedoptimizationproblems,nonlinearprogramming,multi-objectiveoptimization,stochastic programmingandcombinatorialoptimizationproblems.PSOhasbeenpresentedintheliterature andappliedsuccessfullyinreallifeapplications.Inthispaper,acomprehensivereviewofPSOas awell-knownpopulation-basedoptimizationtechnique.Thereviewstartsbyabriefintroductionto thebehaviorofthePSO,thenbasicconceptsanddevelopmentofPSOarediscussed,it’sfollowed bythediscussionofPSOinertiaweightandconstrictionfactoraswellasissuesrelatedtoparameter setting, selectionand tuning,dynamicenvironments, andhybridization.Also,we introduced the otherrepresentation,convergencepropertiesandtheapplicationsofPSO.Finally,conclusionsand discussionarepresented.Limitationstobeaddressedandthedirectionsofresearchinthefutureare identified,andanextensivebibliographyisalsoincluded.

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粒子群优化从理论到应用

粒子群优化(PSO)被认为是群中最重要的方法之一intelligence.PSOisrelatedtothestudyofswarms;whereitisasimulationofbirdflocks。Itcanbe usedtosolveawidevarietyofoptimizationproblemssuchasunconstrainedoptimizationproblems, constrainedoptimizationproblems，nonlinearprogramming，multi-objectiveoptimization，stochastic programmingandcombinatorialoptimizationproblems。PSOhasbeenpresentedintheliterature andappliedsuccessfullyinreallifeapplications。Inthispaper，acomprehensivereviewofPSOas awell-knownpopulation-basedoptimizationtechnique。Thereviewstartsbyabriefintroductionto thebehaviorofthePSO，thenbasicconceptsanddevelopmentofPSOarediscussed，it 'sfollowed bythediscussionofPSOinertiaweightandconstrictionfactoraswellasissuesrelatedtoparameter设置，selectionand调优，dynamicenvironments, andhybridization。Also，we介绍了> > otherrepresentation，convergencepropertiesandtheapplicationsofPSO。Finally，conclusionsand discussionarepresented。Limitationstobeaddressedandthedirectionsofresearchinthefutureare确定，andanextensivebibliographyisalsoincluded。

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来源期刊

Int. J. Rough Sets Data Anal.

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