Vol.3,No.3王芳等：带时间窗的多目标蔬菜运输配送路径优化算法
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lemsoflongtransportationtime,hightotaltransportationcostandshortpreservationtimeofvegetablesduringtransportation,
consideringtheconstraintssuchasvehicleloadandtimewindow,thisstudyproposedageneticsimulatedannealingalgorithm
(GA-SA)formulti-objectivevegetabledistributionpathoptimizationwithtimewindows.Thatwas,thesimulatedannealingal‐
gorithm(SA)adaptive(Metropolis)acceptancecriterionwasintroducedintotheoperationprocessofgeneticalgorithm(GA).
Thebasicideawas:First,theoriginalpopulationwasselected,crossedandmutatedbygeneticalgorithmtoformanewgenera‐
tionofpathpopulation.Atthistime,byintroducingmetropolisacceptancecriterion,andthen,aftermodifyingthesubsituation
ofthenewgenerationpathpopulationandselectingcrossmutation,anewtargetpathpopulationwasobtained.Theimprovedal‐
gorithmretainedtheexcellentindividual,andtheconvergencespeed,jumpedoutofthelocaloptimalsolutionfoundbasedon
geneticalgorithm,andthenfoundtheglobaloptimalsolution.Then,themulti-objectiveofreturningallvehiclestothedistribu‐
tioncenterafterdistributionwastheleasttime-consuming,thelowestcostandtheleastuseofvehicleswasachieved,andthe
optimalpathofvegetabletransportationwasobtained.TakingBaodingcityinHebeiprovinceasthedistributioncenterand
sometownsunderthejurisdictionofBaodingcityasthedistributionpoints,theexperimentofvegetabletransportationpathop‐
timizationwasdesigned.Theexperimentsofgeneticalgorithm,simulatedannealingalgorithmandgeneticsimulatedannealing
algorithmwerecarriedout,respectively.Thecomparativeanalysiswascarriedoutfromtheaspectsofconvergencespeed,total
distance,totaltime,vehiclesandtotalcost.Theexperimentalresultsshowedthat,comparedwiththegeneticalgorithmandsim‐
ulatedannealingalgorithm,GA-SAcouldeffectivelyaccelerateitsconvergencespeed.Thetotalcostoftheoptimizeddistribu‐
tionroutereducedbyabout23.7%and4%respectively,thetotaldistancereducedby22.6%and3%respectively,thetimecon‐
sumptionreducedby26.2and2.6hoursrespectively,and2and1vehicleswereusedlessrespectively.Thisstudycouldalso
providereferencefortheresearchofcoldfreshfoodandothertransportationpathoptimization.
Keywords:geneticalgorithm;Metropolisguidelines;vehicleroutingproblem;vegetabletransportation;simulatedannealingal‐
gorithm;timeconsuming;cost;pathoptimization
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