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1、AbstractMixed-modelassemblylinebalancingproblemisakeytechnologicalproblemwhichthemanufacturingmustface.Solutiontotheproblemdirectlyaffectstheproductionefficiencyandthecostofproduct.Throughreasonableimprovement,ononehand,theequipmentutilizationofenterprisecanbemaximized,on
2、theotherhand,thewasteofresourcescanbereduced,thusrealizingleanmanufacturing.However,duetothelargevarietyofproducts,thevariableproportionofeachtype,thedifferencesoftasksandtasktime,mixed-modelassemblylinebalancingproblemismorecomplexthanthatofsingle-model.Therefore,conduct
3、ingresearchonmixed-modelassemblylinebalancingproblemisoftheoreticalsignificanceandeconomicvalue.Inthispaper,accordingtothecharacteristicsofmixed-modelassemblylinebalancingproblem,multipleevaluationfunctionthatisclosetotheactualproductionprocessisestablishedwithconsidering
4、theinfluencefactorsofproduction.Inaddition,basedonIWDalgorithm,solvingmethodtomulti-objectivemixed-modelassemblylinebalancingproblemisputforward.Themainworkdoneisasfollows:(1)IWDalgorithmisintroducedintomixed-modelassemblylinebalancingproblemareas:First,theencodingrules,l
5、ocalsoilupdaterulesandglobalupdaterulesareimproved.Then,inordertoincreasetheglobaloptimizationabilityofthealgorithm,thenodeselectionruleisredefinedbyjoiningthelargestprobabilityselectionruleandrandomsearchrule,thusforminghybridselectionmechanism.Finally,theeffectivenessof
6、theimprovedIWDalgorithmisverifiedthroughseveralstandardproblems.What'smore,comparedwithgeneticalgorithm,experimentalresultsshowthatsolvingrateandtheeffectofIWDalgorithmissuperior.(2)Mathematicalmodelofmulti-objectivemixed-modelassemblylinebalancingproblemisestablishedbyin
7、tegratingmaximaltaskrelatedness,minimumworkstationnumberandminimumworkloadbalancecoefficient,sothatthemodelisconsistentwiththeactualproductionprocess.Formulti-objectivemixed-modelassemblylinebalancingproblem,themethodofParetodominantsortingisusedtoevaluatemultipletargets.
8、ThenonthebasisofthesortingresultsIWDalgorithmwasimprovedtoincreasetheglobaloptimizationability.F
