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1、EuropeanJournalofOperationalResearch214(2011)223–231ContentslistsavailableatScienceDirectEuropeanJournalofOperationalResearchjournalhomepage:www.elsevier.com/locate/ejorProduction,ManufacturingandLogisticsAreducedvariableneighborhoodsearchalgorithmforuncapacitatedmult
2、ilevellot-sizingproblemsabc,⇑cYiyongXiao,IkouKaku,QiuhongZhao,RenqianZhangaSchoolofReliabilityandSystemEngineering,BeihangUniversity,Beijing100191,ChinabDepartmentofManagementScienceandEngineering,AkitaPrefecturalUniversity,Yulihonjo,Akita015-0055,JapancSchoolofEconom
3、icsandManagement,BeihangUniversity,Beijing100191,ChinaarticleinfoabstractArticlehistory:Multilevellot-sizing(MLLS)problems,whichinvolvecomplicatedproductstructureswithinterdepen-Received29July2010denceamongtheitems,playanimportantroleinthematerialrequirementplanning(M
4、RP)systemofAccepted19April2011modernmanufacturing/assemblinglines.Inthispaper,wepresentareducedvariableneighborhoodAvailableonline27April2011search(RVNS)algorithmandseveralimplementaltechniquesforsolvinguncapacitatedMLLSproblems.Computationalexperimentsarecarriedouton
5、threeclassesofbenchmarkinstancesunderdifferentKeywords:scales(small,medium,andlarge).Comparedwiththeexistingliterature,RVNSshowsgoodperformanceMeta-heuristicsandrobustnessonatotalof176testedinstances.Forthe96small-sizedinstances,theRVNSalgorithmUncapacitatedmultilevel
6、lot-sizing(MLLS)canfind100%oftheoptimalsolutionsinlesscomputationaltime;forthe40medium-sizedandthe40problemMaterialrequirementplanning(MRP)large-sizedinstances,theRVNSalgorithmiscompetitiveagainstothermethods,enjoyinggoodeffective-Reducedvariableneighborhoodsearchnessa
7、swellashighcomputationalefficiency.Inthecalculations,RVNSupdated7(17.5%)bestknown(RVNS)algorithmsolutionsforthemedium-sizedinstancesand16(40%)bestknownsolutionsforthelarge-sizedProductionplanninginstances.Ó2011ElsevierB.V.Allrightsreserved.1.Introductionofsingle-levell
8、ot-sizingmodelstoeachcomponentoftheproductstructure(Yelle,1979;VeralandLaForge,1985),andlater,oftheMaterialrequirementplanni
