面向城市末端共同配送的電動(dòng)物流車路徑—定價(jià)博弈聯(lián)合決策研究面向城市末端共同配送的電動(dòng)物流車路徑—定價(jià)博弈聯(lián)合決策研究

摘要：城市末端配送服務(wù)的規(guī)模和范圍不斷擴(kuò)大，對(duì)物流車輛的路徑與定價(jià)研究提出了新挑戰(zhàn)。針對(duì)此問題，本文提出了一種面向城市末端共同配送的電動(dòng)物流車路徑—定價(jià)博弈聯(lián)合決策模型。該模型主要考慮了市場多方博弈參與、電動(dòng)物流車輛的路徑選擇和價(jià)格定價(jià)等關(guān)鍵因素。首先，通過對(duì)市場參與者的分析和綜合評(píng)估，建立了電動(dòng)物流車輛的市場博弈模型，從而確定租賃價(jià)格和租賃合同條款。其次，采用混合整數(shù)線性規(guī)劃方法，在考慮車輛輛載限制等因素的前提下，得到了電動(dòng)物流車的路徑解決方案。最后，將路線和定價(jià)結(jié)果進(jìn)行集成，并根據(jù)書包算法進(jìn)行優(yōu)化，得到最終的共同配送方案，并進(jìn)行仿真實(shí)驗(yàn)，結(jié)果表明該算法可以有效提高共同配送系統(tǒng)的效率，降低配送成本。

關(guān)鍵詞：城市末端配送；電動(dòng)物流車；路線規(guī)劃；價(jià)格定價(jià)；博弈模型

Abstract:Thescaleandscopeofurbanend-to-enddeliveryservicesarecontinuouslyexpanding,bringingnewchallengestotheresearchonthepathandpricingoflogisticsvehicles.Inresponsetothisproblem,thispaperproposesacombineddecision-makingmodelforpath-pricinggameofelectriclogisticsvehicles,whichisorientedtowardstheend-to-endjointdeliveryofurbancities.Themodelmainlyconsiderskeyfactorssuchasmarketmulti-partygames,pathselectionofelectriclogisticsvehicles,andpricing.First,byanalyzingandcomprehensivelyevaluatingmarketparticipants,anelectriclogisticsvehiclemarketgamemodelisestablishedtodetermineleasepricesandleasecontractterms.Secondly,usingmixedintegerlinearprogrammingmethod,thepathsolutionofelectriclogisticsvehiclesisobtainedunderthepremiseofconsideringfactorssuchasvehicleloadrestrictions.Finally,therouteandpricingresultsareintegrated,optimizedaccordingtothebookbagalgorithm,andthefinaljointdeliveryplanisobtained.Simulationexperimentsarecarriedout,andtheresultsshowthatthisalgorithmcaneffectivelyimprovetheefficiencyofthejointdeliverysystemandreducedeliverycosts.

Keywords:urbanend-to-enddelivery;electriclogisticsvehicles;routeplanning;pricing;gamemodelAsthedemandforfastandefficienturbanend-to-enddeliveryincreases,theuseofelectriclogisticsvehiclescomesintoplay.However,thehighdeliverycostsandcomplexlogisticssystemposeachallengefortheefficientoperationofthedeliverysystem.Inordertoaddressthisissue,ajointdeliverysystemwasproposed,wheredifferentlogisticscompaniessharethesameelectricvehiclefleetandjointlyplantheirdeliveryroutes.

Toachieveanoptimaljointdeliveryplan,abookbagalgorithmisintegratedintorouteplanningandpricingstrategies.Thebookbagalgorithmisamathematicalmodelusedtooptimizeplanningthatinvolveslimitingthenumberofitemsthatcanbeselectedfordelivery.Thisalgorithmisthenusedtooptimizetheroutesandpricingstrategiesbyconsideringvariablessuchasdistance,traffic,deliverytimewindowrestrictions,andvehicleloadrestrictions.

Anadditionalaspectofthejointdeliverysystemistheuseofagamemodel.Thegamemodelhelpstooptimizepricingstrategiesforeachlogisticscompanywhileensuringoverallprofitabilityfortheentireoperation.Eachlogisticscompanyplaysaroleindeterminingthepricingofthejointdelivery,andthegamemodelensuresthateachcompanyreceivesasatisfactoryprofitwhilemaintainingtheoverallprofitabilityofthesystem.

Insummary,theproposedalgorithm,combiningthebookbagalgorithmandthegamemodel,effectivelyoptimizesthejointdeliverysystembyreducingcostsandincreasingefficiency.Thesimulationresultsshowedthatthisalgorithmishighlyefficientandcost-effective,makingitaviableoptionforurbanend-to-enddeliveryoperationsMoreover,theproposedalgorithmhasthepotentialtosignificantlyreducethenumberofdeliveryvehiclesontheroad,consequentlyreducingtrafficcongestionandemissions.Italsohastheabilitytoimprovecustomersatisfactionbyofferingfastandreliabledeliveryservices.

However,therearesomelimitationstotheproposedalgorithmthatneedtobeaddressed.Firstly,thealgorithmassumesthatallpackagesareofequalweightandsize,whichmaynotbethecaseinreality.Thisassumptionmayleadtoinefficientuseofdeliveryvehiclesandresources,ultimatelyincreasingcosts.Therefore,furtherresearchisneededtodevelopanalgorithmthatcaneffectivelyhandlepackagesofvaryingsizesandweights.

Secondly,thealgorithmassumesthatallcompanieshavethesameobjectivefunction,whichistomaximizetheirprofits.However,inreality,thismaynotalwaysbethecase.Differentcompaniesmayhavedifferentobjectives,suchasmaximizingcustomersatisfactionorreducingdeliverytime.Therefore,futureresearchshouldexplorethedevelopmentofanalgorithmthatcanhandlesuchvariedobjectives.

Lastly,theproposedalgorithmdoesnotaccountforexternalfactorssuchasweather,trafficconditions,orroadclosures,whichmayimpactthedeliveryschedulesandoverallefficiencyofthesystem.Therefore,furtherresearchisneededtodevelopanalgorithmthatcanadapttosuchunforeseenscenariosandoptimizethedeliveryprocessaccordingly.

Overall,theproposedalgorithmhasthepotentialtorevolutionizetheend-to-enddeliveryoperationsinurbanareasbyimprovingefficiency,reducingcosts,andenhancingcustomersatisfaction.However,furtherresearchisneededtoaddressthelimitationsandoptimizethealgorithmforreal-worldapplicationOneimportantaspectthatshouldbeconsideredwhenimplementingtheproposedalgorithmistheneedfordataprivacyandsecurity.Withthecollectionofsensitiveinformationsuchascustomeraddresses,itiscrucialtoensurethatpropermeasuresaretakentoprotectthisdatafromunauthorizedaccessandmisuse.Thiscanbeachievedthroughtheuseofsecurecommunicationprotocolsandencryptiontechniquestoprotectthedatabothduringtransmissionandstorage.

Anotherfactorthatshouldbetakenintoconsiderationisthepotentialimpactofthealgorithmontheworkforce.Asthealgorithmaimstooptimizethedeliveryprocess,itmayleadtoadecreaseinthenumberofrequiredworkersorchangesintheirrolesandresponsibilities.Therefore,itisimportanttoanticipateanypotentialchangesintheworkforceandtakemeasurestoensureasmoothtransitionfortheworkers.

Furthermore,theproposedalgorithmmayfacesomelegalandregulatorychallenges.Forexample,theremayberegulationsregardingtheuseofautonomousvehiclesordronesfordeliverypurposesinurbanareas.Itisimportanttoensurethatthealgorithmcomplieswithallrelevantlawsandregulations,andworkwithregulatorybodiestoovercomeanypotentialchallenges.

Inconclusion,theproposedalgorithmhasthepotentialtorevolutionizetheend-to-enddeliveryoperationsinurbanareas.However,furtherresearchisneededtooptimizethealgorithmforreal-worldapplicationandaddressthelimitationsandchallengesthatcomewithit.Withproperplanningandconsideration,thealgorithmcanhelptoimproveefficiency,reducecosts,ande