流水车间成组工件调度问题的多目标优化算法-豆柴文库

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流水车间成组工件调度问题的多目标优化算法
流水车间成组工件调度问题的多目标优化算法
Abstract:
Thegroupschedulingproblemintheflowshopisaproblemthatneedstobesolvedinmanufacturingplants.Thepurposeofthisproblemistooptimizetheflowofworkandgroupscheduling.Thisoptimizationcanleadtoincreasedproductivityandreducedproductioncosts.Thispaperwillexplorethemulti-objectiveoptimizationalgorithmforthegroupschedulingproblemintheflowshop.
Introduction:
Thegroupschedulingproblemintheflowshopisaproblemthatneedstobeaddressedbyanymanufacturingplant.Thisproblemaffectstheflowofworkandhowworkisgroupedtogether.Byoptimizingthisflow,companiescanreduceproductioncostsandincreaseproductivity.However,thisisnotaneasyproblemtosolve,astherearemanydifferentfactorstoconsider.
Themulti-objectiveoptimizationalgorithmisoneapproachthatcanbeusedtosolvethisproblem.Thisapproachinvolvesconsideringmultipleobjectiveswhenmakingschedulingdecisions.Thiscanhelpbalanceconflictingobjectivesandprovideamoreoptimalsolution.
LiteratureReview:
Therehasbeenalotofresearchconductedonthegroupschedulingproblemintheflowshop.Avarietyofalgorithmshavebeenproposedtosolvethisproblem,includingheuristics,metaheuristics,andmulti-objectiveoptimizationalgorithms.
Oneofthemostcommonapproachesistheuseofheuristics.Heuristicsaremethodsthatareusedtoquicklyfindagoodsolution,althoughtheydonotguaranteeanoptimalresult.Someofthecommonlyusedheuristicsincludetheshortestprocessingtimefirst(SPT)andtheJohnsonalgorithm.
Metaheuristicsareoptimizationtechniquesthatuseaniterativeprocesstoexplorethesearchspaceandfindagoodsolution.Someofthecommonlyusedmetaheuristicsincludegeneticalgorithms,simulatedannealing,andtabusearch.
Multi-objectiveoptimizationalgorithmshavegainedpopularityinrecentyears.Thesealgorithmsconsidermultipleobjectivesatthesametime,whichcanhelpreduceproductioncostsandincreaseproductivitysimultaneously.Oneofthemostcommonmulti-objectiveoptimizationalgorithmsistheParetooptimalityalgorithm.
Methodology:
Inthisstudy,wewilluseamulti-objectiveoptimizationalgorithmtosolvethegroupschedulingprobl