一种基于动态拓扑结构的PSO改进算法-豆柴文库

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一种基于动态拓扑结构的PSO改进算法
Title:ADynamicTopology-basedImprovedParticleSwarmOptimization(PSO)Algorithm
Abstract:
ParticleSwarmOptimization(PSO)isapopularpopulation-basedoptimizationalgorithminspiredbythesocialbehaviorofbirdsandfishes.TraditionalPSOfaceschallengeswhensolvingcomplexoptimizationproblems,suchasprematureconvergenceandlackofdiversity.Inthispaper,weproposeanovelPSOalgorithmbasedondynamictopologyandimprovedparticleupdatestrategiestoovercometheselimitations.Thealgorithmdynamicallyadjuststheparticleneighborhoodstructureandintroducesanewparticleupdateruleutilizinghistoricalbestaswellasglobalbestinformation.ExperimentalresultsonbenchmarkfunctionsdemonstratetheeffectivenessandefficiencyoftheproposedalgorithmcomparedtotraditionalPSOalgorithmsandotherstate-of-the-artoptimizationtechniques.
1.Introduction
ParticleSwarmOptimization(PSO)isapopularheuristicoptimizationalgorithmthatsimulatesthesocialbehaviorofbirdsflockingorfishesschoolingtofindoptimalsolutions.PSOhasbeensuccessfullyappliedinvariousdomains,suchassignalprocessing,imageclassification,androbotics.However,traditionalPSOispronetoprematureconvergenceandlacksdiversity,leadingtosuboptimalsolutionsforcomplexoptimizationproblems.Inordertoovercometheselimitations,thispaperintroducesanovelPSOalgorithmthatintegratesdynamictopologyandimprovedparticleupdatestrategies.
2.RelatedWork
ThissectionprovidesacomprehensivereviewofexistingPSOalgorithmsandtheirlimitations.TraditionalPSOalgorithmisbasedonafixedtopologywhereparticlesinteractwithapredefinedsetofneighbors.SeveralapproacheshavebeenproposedtoenhancetheperformanceoftraditionalPSO,includingaddingdiversitythroughmutationoperatorsorintroducingadaptiveinertiaweights.However,thesemethodsstillfailtoaddresstheproblemofprematureconvergenceeffectively.
3.DynamicTopology-basedPSO
TheproposedalgorithmintroducesadynamictopologymechanismtoimprovetheexplorationandexploitationcapabilitiesofthePSOalgorithm.Theparticleneighborhoodstructureisupdateddynamicallyduringtheoptimizationprocessbased