基于ROI,VMI和CS三种库存方式长短期绩效的对比研究

ROI、VMI和Cs是基于供应链的三种库存管理方式.本文以两层供应链的ROI、VMI和CS方式为例,通过数学模型和具体算例,比较分析了三种库存方式下买方和卖方成本和利润构成的不同之处.本文研究发现:在长期内相对于ROI方式而言,VMI方式下供应链的效率更高;如果卖方的单位存储成本大于买方,CS方式下供应链的长短期效率可能高于VMI更高于ROI方式.     

带批次和临时库存的越库配送车辆路径问题研究

从零售业供应链整合入手,构建供应商、配送中心和零售点构成的协同配送网络,研究带批次和临时库存的越库配送车辆路径问题.将越库过程分为取货、分拣和配货三个阶段,考虑配送中心分拣能力,分批次设置车辆协同到达配送中心的服务时刻,据此建立以最小化车辆运输成本、临时库存成本和固定成本为目标的数学模型.考虑问题特征,设计一种混合变邻域搜索粒子群算法求解,并将结果进行横纵向比较.结果表明,所提算法有效且可靠,能够为带批次和临时库存的越库配送问题提供解决方案.     

快速补货模式下的动态定价与库存联合策略

在供应有限的情况下,研究常规补货和快速补货下商品动态定价问题.首先,建立了动态规划模型,理论证明了最优库存策略是基于(s,S)策略下改进的基本库存策略.其次,提出了一种启发式策略求复杂系统的最优策略,启发式算法能够求出最优价格和最优库存水平.最后,数值算例研究表明,库存管理中采用快速补货提高了零售商的利润;初始库存水平越高零售商的利润越高.     

基于两层供应链的VMI系统可行性分析研究

一般来说，供应商管理用户库存（VMI）能够给购买方带来更高的利润，而对供货方的影响却是不确定的。而现实中很多VMI策略都是由购买方主导的，购买方一般不愿和供货方分享收益，因此供货方必须自己判断是否接受VMI策略。本文在基于对安徽奇瑞汽车集团的零部件库存进行的调查的基础上，对VMI系统可行性分析的研究分两步进行：（1）假设供货方已经接受了购买方主导的VMI策略，它如何制定自己的最优送货策略；（2）通过比较供货方分别在RMI和VMI下的最小成本，供货方决定是否接受购买方主导的VMI策略。     

随机需求下供应商管理库存的供应链模型

以一个供应商和一个零售商的两阶段供应链为背景,利用报童模型给出了供应商管理库存(VMI)的供应链模型,在需求服从均匀分布的条件下得出解析解,并与传统的零售商管理库存(RMI)系统作了比较,分析了这两种情况下批发价和订货量的变化.数值结果表明VMI导致了批发价的缩减,但提高了订货量,VMI减轻了双重边际效应,系统利润多于传统的RMI系统.     

在允许缺货情况下的易变质产品供应商管理库存

本首先通过解析推导给出了一个考虑一个供应商和多个不同的订货商，并且允许订货商缺货的易腐商品供应商管理库存VMI(Vendor Managed Inventory)模型；其次通过mathematica4．2软件计算。给出了算例及其最优解，并通过灵敏度分析讨论了单位缺货成本和变质率对库存决策的影响；最后给出了总结，说明了研究的意义。     

服务水平约束下动态定价与库存管理

本文研究服务水平约束下的动态定价与库存管理问题。企业在有限期内销售某种产品,产品的需求为随机需求,且期望需求依赖于产品价格。在每一期期初,企业需要在满足服务水平约束的条件下同时决定订货量和产品价格。本文首先构建了动态定价和订购联合决策的随机动态规划模型,并证明了最优解的存在性。进一步,通过对最优解的结构进行刻画,将原问题的求解转化为若干子问题的求解,降低了问题求解的难度。通过对最优解的分析发现,当期初库存增大时,产品最优价格降低。通过分析目标服务水平对利润的影响,证明了服务水平与利润之间存在权衡,实现高的服务水平需要承受利润损失。数值模拟表明,相对于传统的静态定价策略,采用动态定价策略可以降低追求服务水平所带来的利润损失,验证了动态定价策略的有效性。     

基于动态遗传算法的共享配送模式研究

针对传统配送中配送车辆装载率低、车辆数量多及配送成本高等问题,提出不同类型零售商资源共享的城市配送优化方法,并考虑配送中的车辆油耗与不确定需求等问题。以总配送成本最低为目标建立模型,利用基于动态参数的改进遗传算法对模型进行求解。最后,通过算例对共享配送模式与算法进行测试。结果表明,共享配送模式能够有效减低车辆数量、提高装载率及降低配送成本,同时改进遗传算法能够高效、准确对模型求解。     

基于贝叶斯信息更新的动态库存与定价研究

考虑价格对需求量的扰动并利用贝叶斯公式对需求分布函数中的未知参数进行不断学习更新,研究缺货部分比例延迟交货情形下的动态库存与动态定价问题,刻画了最优利润函数的性质并证明了"基准库存列表价格"是最优的库存价格水平,并由此得到了最优的补货策略和定价策略。     

考虑越库作业的连锁超市配送路径优化研究

针对大型连锁超市物流配送成本较高的问题,通过分析连锁超市的实际情况和越库作业的实施要求,提出越库配送运作模式.以车辆运输成本、操作成本和库存持有成本最小化为目标,建立带有多越库配送中心的车辆路径模型,将配送过程分为集货、送货两阶段,同时,考虑到产品种类需求的多样化,采取集货过程车辆协同进行和送货过程车辆需求拆分的方式.针对问题的特点设计了一个求解的遗传算法,通过扫描算法优化初始种群,最后结合算例对模型和算法进行验证分析.结果表明,越库作业能有效地提高连锁超市的运作效率,降低超市物流成本.     

供应商管理库存的渠道利润优化分析

本文研究了供应链管理的渠道利润问题。对有确定需求、有初始库存和库存短缺的一种畅销商品,建立了供应商管理库存的渠道利润模型。通过对此模型的进一步分析,证明了在短期激励下供应商管理库存的渠道利润优于一般库存的渠道利润;也证明了在长期激励下,供应商管理库存可以产生比短期激励下更优的渠道利润,也优于一般库存的渠道利润。这一结果对于供应链环境下的库存管理在理论和工程上具有实际意义。     

求解硬时间窗约束下随机需求库存-路径问题的优化算法

随机需求库存-路径问题(Stochastic Demand Inventory Routing Problem, SDIRP)即考虑随机需求环境下供应链中库存与配送的协调优化问题,是实施供应商管理库存策略过程中的关键所在,也是典型的NP难题之一。文章以具有硬时间窗约束的随机需求库存-路径问题(Stochastic Demand Inventory Routing Problem with Hard Time Windows, SDIRPHTW)为研究对象,将SDIRPHTW分解为直接配送的随机库存-路径问题和具有硬时间窗约束的路径优化问题两个子问题,并以最小化系统运行成本和用车数量为目标,设计了一个基于(s,S)库存策略和修正C-W节约法的启发式算法。最后,通过相应的数值算例验证了算法的有效性。     

A Stackelberg game and its improvement in a VMI system with a manufacturing vendor

Vendor managed inventory (VMI) is an inventory management strategy to let a vendor manage his retailers’ inventories, which makes the vendor have the opportunity to obtain some inventory and market-related information of his retailers. This paper discusses how the vendor can take advantage of this information for increasing his own profit by using a Stackelberg game in a VMI system. The vendor here is a manufacturer who procures raw materials to produce a finished product and supplies it at the same wholesale price to multiple retailers. The retailers then sell the product in independent markets at retail prices. Solution procedures are developed to find the Stackelberg game equilibrium that each enterprise is not willing to deviate from for maximizing his own profit. The equilibrium makes the manufacturer benefited, and the retailers’ profits maximized. The equilibrium can then be improved for further benefiting the manufacturer and his retailers if the retailers are willing to cooperate with the manufacturer by using a cooperative contract. Finally, a numerical example and the corresponding sensitivity analysis are given to illustrate that: (1) the manufacturer can benefit from his leadership, and monopolize the added profit of the VMI system in some cases; (2) The manufacturer can further improve his own profit, and then the retailers’ profits by the cooperative contract, as compared to the Stackelberg equilibrium; (3) market and raw material related parameters have significant influence on every enterprise’s net profit.     

Minimizing the Total Cost in an Integrated Vendor—Managed Inventory System

In this paper we consider a complex production-distribution system, where a facility produces (or orders from an external supplier) several items which are distributed to a set of retailers by a fleet of vehicles. We consider Vendor-Managed Inventory (VMI) policies, in which the facility knows the inventory levels of the retailers and takes care of their replenishment policies. The production (or ordering) policy, the retailers replenishment policies and the transportation policy have to be determined so as to minimize the total system cost. The cost includes the fixed and variable production costs at the facility, the inventory costs at the facility and at the retailers and the transportation costs, that is the fixed costs of the vehicles and the traveling costs. We study two different types of VMI policies: The order-up-to level policy, in which the order-up-to level quantity is shipped to each retailer whenever served (i.e. the quantity delivered to each retailer is such that the maximum level of the inventory at the retailer is reached) and the fill-fill-dump policy, in which the order-up-to level quantity is shipped to all but the last retailer on each delivery route, while the quantity delivered to the last retailer is the minimum between the order-up-to level quantity and the residual transportation capacity of the vehicle. We propose two different decompositions of the problem and optimal or heuristic procedures for the solution of the subproblems. We show that, for reasonable initial values of the variables, the order in which the subproblems are solved does not influence the final solution. We will first solve the distribution subproblem and then the production subproblem. The computational results show that the fill-fill-dump policy reduces the average cost with respect to the order-up-to level policy and that one of the decompositions is more effective. Moreover, we compare the VMI policies with the more traditional Retailer-Managed Inventory (RMI) policy and show that the VMI policies significantly reduce the average cost with respect to the RMI policy.     

A practical solution approach for the cyclic inventory routing problem

Vendor managed inventory (VMI) is an example of effective cooperation and partnering practices between up- and downstream stages in a supply chain. In VMI, the supplier takes the responsibility for replenishing his customers’ inventories based on their consumption data, with the aim of optimizing the over all distribution and inventory costs throughout the supply chain. This paper discusses the challenging optimization problem that arises in this context, known as the inventory routing problem (IRP). The objective of this IRP problem is to determine a distribution plan that minimizes average distribution and inventory costs without causing any stock-out at the customers. Deterministic constant customer demand rates are assumed and therefore, a long-term cyclical approach is adopted, integrating fleet sizing, vehicle routing, and inventory management. Further, realistic side-constraints such as limited storage capacities, driving time restrictions and constant replenishment intervals are taken into account. A heuristic solution approach is proposed, analyzed and evaluated against a comparable state-of-the-art heuristic.     

Vendor managed inventory contracts – coordinating the supply chain while looking from the vendor’s perspective

The paper studies coordination of a supply chain when the inventory is managed by the vendor (VMI). We also provide a general mathematical framework that can be used to analyze contracts under both retailer managed inventory (RMI) and VMI. Using a simple newsvendor scenario with a single vendor and single retailer, we study five popular coordinating supply chain contracts: buyback, quantity flexibility, quantity discount, sales rebate, and revenue sharing contracts. We analyze the ability of these contracts to coordinate the supply chain under VMI when the vendor freely decides the quantity. We find that even though all of them coordinate under RMI, quantity flexibility and sales rebate contracts do not generally coordinate under VMI. Furthermore, buyback and revenue sharing contracts are equivalent. Hence, we propose two new contracts which coordinate under VMI (one of which coordinates under RMI too, provided a well-known assumption holds). Finally, we extend our analysis to consider multiple independent retailers with the vendor incurring linear or convex production cost, and show that our results are qualitatively unchanged.