预览加载中，请您耐心等待几秒...

拆卸线平衡问题的改进细菌觅食优化算法.docx

预览
1/2
2/2

在线预览结束，喜欢就下载吧，查找使用更方便

下载提示 文本预览

如果您无法下载资料，请参考说明：

1、部分资料下载需要金币，请确保您的账户上有足够的金币

2、已购买过的文档，再次下载不重复扣费

3、资料包下载后请先用软件解压，在使用对应软件打开

拆卸线平衡问题的改进细菌觅食优化算法 Title:ImprovingBacterialForagingOptimizationAlgorithmfortheDisassemblyLineBalancingProblem Abstract: Thedisassemblylinebalancingproblem(DLBP)isacrucialtaskinmanufacturingindustrythataimstooptimizetheefficiencyandproductivityofdisassemblyoperations.Inrecentyears,metaheuristicalgorithmshavebeenwidelyusedtosolveDLBPduetotheirabilitytofindnear-optimalsolutions.ThispaperproposesanimprovedversionoftheBacterialForagingOptimizationAlgorithm(BFOA)specificallydesignedforDLBP.TheEnhancedBacterialForagingOptimizationAlgorithm(EBFOA)combinestheexplorationandexploitationcapabilitiesofBFOAwithadditionalenhancementstoachievebettersolutionqualityandcomputationalefficiency.Theperformanceoftheproposedalgorithmisevaluatedusingasetofbenchmarkinstances,demonstratingitseffectivenessandsuperiorityoverotherexistingalgorithms. 1.Introduction TheDLBPinvolvesbalancingtheworkloadandminimizingthecycletimeindisassemblylines,aimingtooptimizeproductivityandresourceutilization.ThisproblemisknowntobeNP-hard,andthus,theapplicationofefficientandeffectiveoptimizationalgorithmsiscrucial.Inrecentyears,metaheuristicalgorithmshaveattractedsignificantattentionduetotheirabilitytofindnear-optimalsolutionsforcomplexcombinatorialoptimizationproblems.OnesuchalgorithmisBacterialForagingOptimizationAlgorithm(BFOA),inspiredbytheforagingbehaviorofbacteria. 2.BacterialForagingOptimizationAlgorithm BFOAisapopulation-basedmetaheuristicalgorithmthatmimicsbacterialforagingbehaviortosolveoptimizationproblems.Itconsistsofthefollowingfoursteps:(1)Initializationofbacterialpopulation,(2)Chemotaxis,(3)Reproduction,and(4)Eliminationanddispersal. 3.ChallengesinApplyingBFOAtoDLBP AlthoughBFOAhasshownpromisingresultsinvariousoptimizationproblems,certainchallengesarisewhenapplyingittoDLBP.Themainchallengesincludethehighdimensionalityoftheproblem,theneedforbalancingtheworkloadacrossdisassemblystations,andtheminimizationofcycletime. 4.EnhancedBacterialForagingOptimizationAlgorithm(EBFOA) Toaddressthechallengesmentio