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ID:34636279
大小:3.23 MB
页数:62页
时间:2019-03-08
《基于vmi库存和配送联合优化的研究》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、中文摘要摘要:随着物流管理的不断发展与市场竞争的日益激烈,传统企业间的竞争逐渐转变为以供应链为基础的企业间的合作,供应商管理库存(VendorManagedInventory,简称VMI)在这种逐渐转变的过程中得到了越来越广泛的应用。VMI模式的应用使得供应商的决策更具有主动性,为供应商通过统筹规划库存与配送两个物流环节,合理安排库存补充和配送计划,有效降低物流成本提供了新的契机,研究基于VMI的库存与配送联合优化问题具有重要意义。本文针对一个供应商与多个客户组成的二级物流系统,研究了确定需求下基于VMI的库存与配送联合优化问题。首先结合VMI相关理论知识,从供应商的角度对库
2、存控制与配送决策两方面分别进行了深入分析,论证了二者间的关系;其次,在分析系统库存成本与配送成本构成的基础上,建立了以系统总成本最小为目标的基于VMI的库存与配送联合优化模型,设计了求解该模型的迭代算法,从系统优化的角度确定最优库存与配送方案,同时本文在计算配送运输成本时,考虑了整车运输与零担运输两种配送方式,并设计了求解配送优化问题的遗传算法策略;最后通过构造具体算例,运用MATLAB软件进行仿真计算,验证了模型及算法的有效性与合理性。关键词:供应商管理库存;库存与配送;联合优化;迭代算法;遗传算法;分类号:U492.3ABSTRACTABSTRACT:Withthegro
3、winglogisticsmanagementandincreasinglyfiercemarketcompetition,traditionalenterprisecompetitionhasbeenchangedintothecooperationbetweenenterprisesinsupplychain.VendorManagedInventoryhasbeenadoptedbroadlyintheprocessofchange.VMIprovidessuppliersmoreopportunitiestoarrangeforinventoryanddistribu
4、tionreasonablythroughoverallplanningandreducelogisticscost.Theresearchoninventory-distributionintegratedoptimizationhasagreatsignificance.Inthispaper,theinventory-distributionintegratedoptimizationproblemonatwo-echelonlogisticssystemcomposedofasingledistributioncenterandmanysalespointsisstu
5、diedundertheconditionsofVMIstrategyandd.eterminatedemand..Firstly,basedonVMItheory,theauthorseparatelyanalysesinventorycontrolanddistributiondecision-makingandthendescribestherelationshipbetweenthemfromthesupplier’Spointofview;Secondly,consideringbothinventorycostanddistributioncostinlogist
6、icssystem,theauthorconstructsaintegratedoptimizationmodeltominimizingthesystemcostandputsforwardtheiterativealgorithmtosolvethemodel,SOastogettheoptimalsolutionofinventorycontrolanddistributiondecision—making.Atthesametime,distributionisdividedintoTLandLTLtoconsiderinthecalculationofthedist
7、ributioncostandthegeneticalgorithmisdesignedtosolveit.Finally,theauthorselectsanenterpriselogisticssystemasanexampleandUSeSmathematicalsimulationMATLABsoftwaretorealizethisproblem,whichinreturndemonstratesthattheoptimizationmodelandalgorithmiseffectivean
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