外部市场存在替代产品的VMI系统研究

供应商管理用户库存(VMI)作为一种有效的补货机制,能对购买渠道的需求信息做出积极正确的反应.现在对VMI的研究往往集中于单个零售商和单个供应商组成的系统,不考虑VMI系统受市场上其他零售商或供应商的影响.假设市场上多个零售商出售相互之间可替代的产品,某个零售商与其供应商之间应用VMI系统.我们的研究主要有两方面:1)VMI系统是否有助于零售商和供应商组成的供应链在差异产品市场上获得更大的收益;2)供应商和零售商如何决策是否应用VMI系统。     

公平偏好下基于批发价契约的供应链 协调研究

文中基于Nash讨价还价博弈思想建立公平偏好框架,构建公平偏好效用体系,以此为基础对采用批发价契约的报童模型展开行为研究,采用数理模型和数值分析方法分析了零售商和供应商的公平偏好行为对零售商和供应链系统最优订货量的影响,即零售商和供应商同时关注公平时,零售商和供应链系统的最优订货量趋于保守;并发现零售商和供应链系统的最优订货量随零售商的公平偏好程度增加而递减,但随着供应商公平偏好程度增加而递增,且供应链系统最优订货量变化趋势比零售商明显．然后,在此基础上分析比较得到,无论供应商和零售商是否偏好公平,批发价契约都不能实现供应链协调．最后,对批发价、零售价、供应商生产成本、零售商缺货成本和供应商缺货成本进行敏感度分析．     

基于批发价契约的多零售商横向转载的供应链协调

研究了多零售商横向转载的供应链批发价契约协调问题。以包含一个制造商和多个零售商的供应链系统为研究对象,基于批发价契约研究了零售商转载下的供应链协调问题,获取了批发价契约可以协调零售商存在横向转载的供应链的理论证据,并给出了相应的产生供应链协调的条件,详细分析了协调情形下供应链系统最优订货量与多零售商无转载及单报童等情形下的最优订货量之间的关系。进一步研究了制造商与零售商在Stackelberg博弈下,零售商横向转载对制造商收益的影响,并提出了在Stackelberg博弈模型中,批发价契约也有可能促使制造商选择供应链系统最优订货量所对应的批发价格,使得供应链协调,且给出了此种协调产生的具体条件。数值算例则对两种供应链协调情形下的订货量、批发价格及期望收益进行了计算与仿真。研究表明,批发价契约可能会使得多零售商存在转载的供应链实现协调,传统的双重边际化效应将会由于制造商和零售商的理性而被弱化。     

一种考虑广告费对需求影响的供应商管理库存集成模型

降低供应链中处于不同阶段的物料(原材料、在制品以及成品)的库存水平已经成为供应链管理的研究焦点之一。其中供应商管理的库存VMI(vendor-managed-inventory)策略不论在理论上还是在不同企业的实践中都到了广泛的关注。本文首先给出了一个考虑一个供应商和多个不同的订货商,订货商有共同的订货补充期,并且考虑广告费对需求影响的VMI集成模型;其次,给出了模型的相应算法;最后,给出了算例加以说明。     

VMI策略下的综合生产计划研究

本重点研究了在供应链环境下，基于供应商管理客户库存(VMI)策略的供应商综合生产计划问题。模型综合考虑了供应链的存储费用、缺货损失和生产费用，提出供应链总成本最小目标模型，并采用搜索法结合线性规划给出了算例求解和分析结论。     

VMI下供应链应对突发事件的协调策略

研究在VMI下由一个供应商和一个零售商组成的供应链,利用改进的供应链契约来协调应对供应链中的突发事件.供应商管理库存下的供应链正常运作时,供应商和零售商运用剩余补贴契约来使供应链中的利润得到合理分配.然后,讨论了突发事件造成市场需求变大和变小的情况下,供应链不能通过原契约达到协调.进而,对原契约进行了改进,证明了改进后的剩余补贴契约可以使供应链重新达到协调.并用实例分析了供应链就突发事件前后的利润变化情况,说明了剩余补贴契约和改进后的契约的合理性和操作的方便性.     

过度自信零售商供应链得失共享回购契约模型

研究在不确定性条件下由一个理性供应商和一个过度自信零售商组成的供应链协调契约模型.考虑由Wang和Webster(2007)提出的得失共享回购契约,在该契约下得到零售商最优订货量及其性质.进一步证明在一定条件下,该契约能协调供应链.特别地,讨论三类特殊契约模型:回购契约,得失共享批发价契约和批发价契约,发现在高利润条件下回购契约可使供应链协调,而在低利润条件下得失共享批发价契约和批发价契约可使供应链协调.     

部分延期付款下易腐品联合经济订货批量模型

针对易腐品供应链的联合库存决策问题展开研究.假设供应链内存在唯一的供应商和零售商,供应商提供商业信用期给零售商,但零售商需要在收到订货后,立即交付部分货款,且零售阶段由于条件限制,产品存在常数腐败率,而联合决策模型的目标是确定供应商的订货量乘数n和零售商的订货周期使得供应链的总成本最低.通过建立该问题的数学模型,证明了目标函数的性质,说明当给定n时,目标函数在每种情况下都存在唯一最优解.以此为基础,给出了相应的求解算法对该联合批量决策模型进行了求解.最后,结合运作管理实践,并通过数值算例说明了模型的有效性.     

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。     

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.     

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.     

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.     

Optimal selection of retailers for a manufacturing vendor in a vendor managed inventory system

A Vendor Managed Inventory (VMI) system consists of a manufacturing vendor and a number of retailers. In such a system, it is essential for the vendor to optimally determine retailer selection and other related decisions, such as the product’s replenishment cycle time and the wholesale price, in order to maximize his profit. Meanwhile, each retailer’s decisions on her willingness to enter the system and retail price are simultaneously considered in the retailer selection process. However, the above interactive decision making is complex and the available studies on interactive retailer selection are scarce. In this study, we formulate the retailer selection problem as a Stackelberg game model to help the manufacturer, as a vendor, optimally select his retailers to form a VMI system. This model is non-linear, mixed-integer, game-theoretic, and analytically intractable. Therefore, we further develop a hybrid algorithm for effectively and efficiently solving the developed model. The hybrid algorithm combines dynamic programming (DP), genetic algorithm (GA) and analytical methods. As demonstrated by our numerical studies, the optimal retailer selection can increase the manufacturer’s profit by up to 90% and the selected retailers’ profits significantly compared to non-selection strategy. The proposed hybrid algorithm can solve the model within a minute for a problem with 100 candidate retailers, whereas a pure GA has to take more than 1 h to solve a small sized problem of 20 candidate retailers achieving an objective value no worse than that obtained by the hybrid algorithm.     

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.     

Demand disruption and coordination of the supply chain with a dominant retailer

This paper develops two coordination models of a supply chain consisting of one manufacturer, one dominant retailer and multiple fringe retailers to investigate how to coordinate the supply chain after demand disruption. We consider two coordination schedules, linear quantity discount schedule and Groves wholesale price schedule. We find that, under the linear quantity discount schedule, the manufacturer only needs to adjust the maximum variable wholesale price after demand disruption. For each case of the disrupted amount of demand, the higher the market share of the dominant retailer, the lower its average wholesale price and the subsidy will be under the linear quantity discount schedule, while the higher its fraction of the supply chain’s profit will be under Groves wholesale price schedule. When the increased amount of demand is very large and production cost is sufficiently low, linear quantity discount schedule is better for the manufacturer. However, when the production cost is sufficiently large, Groves wholesale price schedule is always better. We also find that the disrupted amount of demand largely affects the allocation of the supply chain’s profit.     

A manufacturer's optimal quantity discount strategy and return policy through game-theoretic approach

This study generalised the traditional quantity discount problem with return contracts, in which a manufacturer promises to refund some fraction of the retailer's wholesale price if an item is returned, as a two-stage game. In the first stage the manufacturer and retailer determine the inventory level cooperatively. In the second stage, the manufacturer bargains with the retailer for quantity discount and return schemes to maintain channel efficiency. A menu of discount–return combinations is proposed for the manufacturer to make inventory decisions. The model developed will demonstrate that the return policy can be considered as mirror images of quantity discount strategy. That is, options with more generous return privileges are coupled with higher wholesale prices, whereas the lowest wholesale price comes with very strict limits on returns and a restocking fee for any returned goods.     

Quantity discounts based on the previous order in a two-period inventory model with demand uncertainty

We examine quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model. The retailer places an order in each of the two periods to meet stochastic demands. The manufacturer gives the retailer a price discount on purchases in the second period in excess of the first-period order quantity (incremental QDP) or a price discount for all units ordered in the second period if the retailer orders more in the second period than in the first period (all-units QDP). We show that the retailer's optimal ordering decision in the second period depends on the sum of initial inventory and previous order quantity. Our computational study suggests that the QDP contract induces the retailer to buy more in the second period but less in the first period, while the increase of the total order quantity may not be significant; and that it increases the manufacturer's profit only when the wholesale margin is large relative to the retail margin.     

具有公平偏好成员的两阶段供应链分析

本论文分析具有公平偏好零售商与制造商组成的供应链,在制造商作为Stackelberg博弈的领导者提供批发价格合同给零售商时,零售商如何确定最优的订货量而制造商如何确定最优的批发价格.当需求满足均匀分布时,研究发现存在均衡的最优订货量以及最优批发价格.本论文也分析了需求分布参数对均衡最优解的影响.最后,通过数值计算对供应链的绩效如何随公平偏好参数变化的问题进行了研究.并且说明公平偏好是零售商获取其对供应链利润分配的一种手段.