基于动态子群策略的改进pso算法与其应用分析

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1、-------西安理工大学硕士学位论文andshowsitssuperiorityinsolvingpracticalproblems.Onthebasisofintroducingthepowerfulteachingandlearningglobalsearchoperator,westudyanddesignanimprovedparticleswarmoptimizationalgorithmwithanewsubgroupsplittingmethodanddynamicsubgroupstrategy.We

2、adoptarandomgroupingstrategyinthenewsubgroupsplittingmethod.WenamethenewalgorithmasDynamicSubgroupStrategyParticleSwarmOptimizationalgorithm(DSSPSO).Toexaminetheeffectivenessoftheproposedalgorithm,itistestedon10benchmarkfunctions.ExperimentalresultsshowthatDSSPS

3、Oisaneffectivemethodtooptimizecomplexfunctions,andperformssignificantlybetterthantheoriginalPSOalgorithmandotherimprovedPSOalgorithmi.e.PSO-wFIPSandUPSO.(1)Inmanypracticaloptimizationproblems,therearesomeconstraintconditions.Swarmintelligencealgorithmshavebeensu

4、ccessfullyappliedforconstrainedoptimizationproblems.However,thedifferencebetweeneachconstraintproblemsdifferinthousandsofways,andweusethepenaltyfunctionmethodtosolvetheconstrainedoptimizationproblemisverydifficulttosettheparametersoftheappropriatefactors.Hencewe

5、introduceanewmechanismtoimprovetheparametersconfiguretermeddynamicpenaltymechanismwhichisconducivetosearchforthemobilefeasiblesolutionregiontoacceleratetheprocessofevolution.Basedonthenewproposedmechanismofdynamicpenalty,weapplytheimprovedDSSPSOalgorithmtosolvec

6、rudeoilblendingproblemwithmulti-constraintconditions.ThenwegivethemainflowofcrudeoilblendingoptimizationproblemusingdynamicpenaltymechanismandDSSPSO.Finally,weusetwotestdatatotestifythevalidityofthemethod,andthetestresultsshowtheeffectivenessofthedynamicpenaltym

7、echanismandDSSPSOalgorithm.Keywords:DSSPSO;DynamicSubgroupStrategy;ConstrainOptimization;DynamicPenalty-----------ii万方数据-----------目录目录1绪论............................................................................................................................

8、..........................................11.1课题研究背景..................................................................................................................