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ID:31953797
大小:4.65 MB
页数:60页
时间:2019-01-29
《产能约束下半导体芯片测试生产线调度优化-研究》由会员上传分享,免费在线阅读,更多相关内容在应用文档-天天文库。
1、西南交通大学硕士研究生学位论文第JI页AbstractTheperformancecheckingofpackagedintegratedcircuitsisnamedsemiconductorfinaltesting.Nowadays,thecostoffinaltestinghasarisentothirtypercentofthetotalcostinintegratedcircuitsmanufacturingduetotheincreaseofintegrationandcomplexity.Thesemiconductorfinaltestinghasbecomeabot
2、tleneckinthedevelopmentofChina'ssemiconductorindustryandattractedtheattentionsofresearchersinmanagementscience,industrialengineeringandautomation.Semiconductormanufactureschedulingisallimportantcombinatorialoptimizationproblemcharacterizedbylarge—scale,reentrant,mixedprocessingmodeandmulti·reso
3、urceconstraints.Foralongtime,researchersconsideredresourceconstraintonlyasmachinecapacityconstraint,assumingotherresourceswereinfinite.Moreover,jobsequencedependentsetuptimeWasrarelyconcernedinresearchesonsemiconductormanufacturescheduling.Therefore,hardlyCaneveryresolutionsappliedtothesemicond
4、uctorfacility.Inthisthesis,theschedulingproblemencounteredinsemiconductorfinaltestingoperationWasresearched,consideringthemultipleresourcesconstraintsandjobsequencedependentsetuptimes。Wesimplifiedtheproblemasaflexibleflowshopschedulingproblemwithtwostages,testandbum-in,toprocessandusedadivide-a
5、nd-conquerstrategytosolveit.Atfirsttwostageswereoptimizedseparately,thentheywereintegratedtoatwo-stageflexibleFlowshopschedulingproblemandacombinatorialparticleswarmoptimizationalgorithmWasdesignedtosolveit。Theschedulingproblemonteststagewasrepresentedbyanidenticalparallelmachineschedulingprobl
6、emwithmultipleresourcesconstraintandjobsequencedependentsetuptimes.Amixedintegerprogrammodelandtwoalgorithms,includingaGeneticAlgorithmandaVariableNeighborhoodSearchalgorithm,wereproposedforthisproblem.Wedescribedtheschedulingproblemonbum—instageasasinglemachineschedulingproblemwithjobsequenced
7、ependentsetuptimesandusedcommercialoptimizationsoftwareandsixdifferentalgorithmstosolveit.Experimentalresultsshowthattheheuristicperformedmuchbetterthanotheralgorithmsonsolvinglarge—scaleproblems.Aslast,wedesignedacombinatorialpar
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