一種針對(duì)高維優(yōu)化問題的混合人工蜂群算法

一種針對(duì)高維優(yōu)化問題的混合人工蜂群算法Title:AHybridArtificialBeeColonyAlgorithmforHigh-DimensionalOptimizationProblemsAbstract:Optimizationproblemsinhigh-dimensionalspacesposesignificantchallengestotraditionaloptimizationalgorithmsduetotheincreasedsearchspaceandcomplexity.Swarmintelligencealgorithms,suchastheArtificialBeeColony(ABC)algorithm,haveshownpromiseinsolvingsuchproblems.However,theperformanceoftheoriginalABCalgorithmtendstodeteriorateasthedimensionalityoftheproblemincreases.Inthispaper,weproposeahybridArtificialBeeColonyalgorithmtoaddressthehigh-dimensionaloptimizationproblemsbyincorporatinglocalsearchandadaptiveoperatorselection.Theproposedalgorithm,namedABC-Hybrid,aimstoimprovetheexplorationandexploitationabilitiesoftheoriginalABCalgorithmtoachievebettersolutionqualityandconvergencespeed.ExperimentalresultsonbenchmarkfunctionsdemonstratethatABC-HybridoutperformstheoriginalABCalgorithmandotherstate-of-the-artoptimizationalgorithmsintermsofsolutionqualityandconvergencespeed.1.IntroductionHigh-dimensionaloptimizationproblemscommonlyariseinvariousfields,includingengineeringdesign,machinelearning,anddatamining.Thecurseofdimensionalitymakesitchallengingfortraditionaloptimizationalgorithmstoefficientlysearchfortheglobaloptimainthevastsearchspace.Swarmintelligencealgorithmshavegainedpopularityfortheirabilitytohandlecomplexandhigh-dimensionaloptimizationproblems.TheOriginalABCalgorithminspiredbytheforagingbehaviorofhoneybeesdemonstratesgoodperformanceforsolvingoptimizationproblems.However,theexplorationabilityoftheABCalgorithmdecreaseswithincreasingdimensions,leadingtoreducedconvergencespeedandsolutionquality.Toovercometheselimitations,thispaperproposesahybridABCalgorithmthatcombineslocalsearchandadaptiveoperatorselectiontoenhancetheperformanceoftheABCalgorithminhigh-dimensionalspaces.2.ArtificialBeeColonyAlgorithmThissectionprovidesabriefoverviewoftheoriginalABCalgorithm,includingtheemployedmodel,employedbees,onlookerbees,andscoutbees.Thealgorithmisbasedontheforagingbehaviorofhoneybeesandusesaheuristicsearchmechanismtoexplorethesolutionspace.3.LimitationsoftheOriginalABCAlgorithminHigh-DimensionalSpacesInhigh-dimensionaloptimizationproblems,theperformanceoftheABCalgorithmdeterioratesduetotheincreasedsearchspaceandreducedexplorationability.ThissectiondiscussesthespecificlimitationsoftheoriginalABCalgorithminhighdimensionsandthereasonsbehindthem.4.ProposedABC-HybridAlgorithmTheABC-HybridalgorithmaimstoovercomethelimitationsoftheoriginalABCalgorithminhigh-dimensionalspaces.Itincorporateslocalsearchtechniques,suchashill-climbingandsimulatedannealing,toimproveexplorationandexploitationabilities.Inaddition,adaptiveoperatorselectionisintroducedtodynamicallyadjusttheexplorationandexploitationbalance.ThissectiondescribesthekeycomponentsandstepsoftheABC-Hybridalgorithm.5.ExperimentalSetupToevaluatetheperformanceoftheABC-Hybridalgorithm,asetofbenchmarkfunctionscommonlyusedinhigh-dimensionaloptimizationproblemsisemployed.Thissectionpresentstheexperimentalsetup,includingparametersettings,probleminstances,andperformanceevaluationmetrics.6.ExperimentalResultsTheexperimentalresultscomparetheperformanceoftheproposedABC-HybridalgorithmwiththeoriginalABCalgorithmandotherstate-of-the-artoptimizationalgorithms.TheresultsdemonstratethattheABC-Hybridalgorithmachievesbettersolutionqualityandfasterconvergencespeedinhigh-dimensionaloptimizationproblems.7.DiscussionandAnalysisThissectionprovidesacomprehensivediscussionandanalysisoftheexperimentalresults.ItdiscussesthestrengthsandweaknessesoftheABC-Hybridalgorithm,aswellaspotentialareasforfurtherimprovement.8.ConclusionTheproposedABC-Hybridalgorithmoffersapromisingsolutionfortacklinghigh-dimensionaloptimizationproblems.Bycombininglocalsearchtechniquesandadaptiveoperatorselection,thealgorithmdemonstratesimprovedexplorationandexploitationabilities.ExperimentalresultsshowthattheABC-HybridalgorithmoutperformstheoriginalABCalgorithmandotheroptimizationalgorithmsonbenchmarkfunctions.Futureresearchshouldfocusonfurtherenhancingthealgorithm'sperformanceandapplyingittoreal-worldapplications.9.ReferencesThissectioncontainsthereferencescitedthroughoutthepaper,includingrelevantworksonswarmintelligence,high-dimensionaloptimization,andtheoriginalABCalgorithm.Overall,thispaperintroducesahybridArtificialBeeColonyalgorithm,namedABC-Hybrid,toaddresshigh-dimensionaloptimizationproblems.Byincorporatinglocalsearchtechniquesandadaptiveoperatorselecti