A framework for decentralized multi-echelon inventory control

We provide a cost structure that can be used for decentralized control of a multi-echelon inventory system with a central warehouse and a number of retailers. This cost structure means that the warehouse, in addition to its local costs, pays a penalty cost for a delay at the warehouse to the retailer facing the delay. A basic assumption is that each installation starts with an initial policy concerning e.g., inventory control and transportation. The installations then play a Stackelberg game with the warehouse being [he leader. By minimizing its local costs according to the suggested cost structure, an installation can reduce its costs. The total system costs are then reduced by the same amount. No installation needs to face higher costs due to policy changes at other installations, since the cost structure satisfies a rationality constraint. If an installation applies its initial policy the local costs are the same as in the initial state, even if the other installations change their policies. If the game is played repeatedly the system will approach a Nash equilibrium but not necessarily the centralized optimal solution. As an example we consider a system with one-for-one ordering retailers.     

Coordinating orders in supply chains through price discounts

In this paper, we examine the issue of order coordination between a supplier and multiple retailers in a decentralized multi-echelon inventory/distribution system where the supplier provides a product to multiple retailers who experience static demand and standard inventory costs. Specifically, we propose and analyze a new policy where a manufacturer, who outsources production to an Original Equipment Manufacturer, offers a price discount to retailers when they coordinate the timing of their orders with the manufacturer's order cycle. We show that our proposed policy can lead to more efficient supply chains under certain conditions, and present a straightforward method for finding the manufacturer's optimal price discount in this decentralized supply chain. A numerical experiment illustrates the managerial implications of our model as well as conditions when a manufacturer should consider adopting such a policy.     

双周期可变供货协议的运转优化模型:以漫友为例

关注一个双周期且存在单一供应商和多个经销商组成的供应链生产和库存的分配优化问题：第1个期间,供应商根据经销商的订单进行生产。从第2期间开始,通过引入一个双周期调整协议,供应商为经销商提供了一个可以在第2期间重新调整库存的机会,即每个经销商可以从供应商那里购买额外库存或销售回多余库存（转运实际发货、收货等交割可在经销商之间进行）。研究运用建立数学模型论证了双周期情况下一个供应商和多个经销商组成的纵向集中而横向分散型系统（半分散型系统）的生产、库存及价格最优均衡模型,接着通过实例数据分析,对完全集中型、半分散型和完全分散型系统转运优化效果进行比较,结果显示,完全集中型优化效果最好(最高13%),但实现难度大;而半分散型是否强于完全分散型系统,取决于调节协议中约定的批发价与生产成本之间的差距因素,差距越小,则半分散型系统的优化效果越强（最高3.39%）。     

资金约束下基于零售商竞争的融资模式对比研究

以单供应商与多个零售商的供应链为研究背景,供应商是供应链上的核心企业,而零售商面临着资金约束,与供应商签订收益共享契约。供应商为中小企业提供两种融资方式：保兑仓融资和延迟支付融资。本文研究两种融资对供应链绩效以及供应链各方的影响,构建单供应商和多零售商的Stackelberg博弈模型,发现保兑仓融资模式能增加零售商的订货量,这两种融资模式在分散型供应链下,供应商都可以设置合适的收益分配系数和批发价格实现在集中型供应链下的协调,并能够保证供应商利润最大化。     

具有随机提前期的库存模型中安全因子的优化

建立了一个二级配送系统库存模型,在零售商和供应商库存均采取连续检查控制策略假设下,针对零售商的提前期随供应商的缺货量随机波动这种情形,分析了供应商和零售商关于其安全因子的决策问题.分别求解并研究了双方在分散决策与合作决策的情形下的最优安全因子模型,并通过算例验证了模型的主要结论.     

On the time-window fulfillment rate in a single-item min-max inventory control system

This paper considers an inventory control system with a constraint on the service level. We focus on a popular service target in practice, the time-window ready rate, which is defined as the percentage of periods in which demands are completely fulfilled within a pre-specified time window. We explore the cost impact of different time-window ready rate settings by proposing evaluation and optimization methods for a single-location single-item min-max (or (s, S)) inventory system. New optimization procedures have been developed because the existing methods, which are based on a Lagrangian multiplier, cannot generally handle the current problem. More specifically, in some cases the time-window ready rate is a complicated function of the re-order point s, which renders existing algorithms inapplicable. Our algorithms are based on the monotone properties of cost and service constraint functions, which allow us to search the optimal policy efficiently within an identified region of policy-parameter values. Numerical experiments show the non-linear trade-off between cost and service, and indicate that extending or shrinking the time window can have a significant impact on the inventory cost.     

The multilocation transshipment problem

We consider a supply chain, which consists of several retailers and one supplier. The retailers, who possibly differ in their cost and demand parameters, may be coordinated through replenishment strategies and transshipments, that is, movement of a product among the locations at the same echelon level. We prove that in order to minimize the expected long-run average cost for this system, an optimal replenishment policy is for each retailer to follow an order-up-to S policy. Furthermore, we demonstrate how the values of the order-up-to quantities can be calculated using a sample-path-based optimization procedure. Given an order-up-to S policy, we show how to determine an optimal transshipment policy, using a linear programming/network flow framework. Such a combined numerical approach allows us to study complex and large systems.     

TPL主导下的生鲜电商三级供应链决策分析

研究由TPL、生鲜电商、生鲜产品供应商组成的三级供应链系统,其中生鲜农产品的市场需求受网上零售价格、安全追溯系统可用性、新鲜度的影响。在TPL主导下,运用Stackelberg博弈模型,分析生鲜电商、生鲜产品供应商不同领导权下的最优决策和最大利润,得出以下结论:生鲜产品供应商作为第二领导下的TPL利润、安全追溯系统可用性、保鲜水平、市场需求均大于其作为第三领导时的情形;不同领导权对供应链企业的利润也会产生影响,利润偏向于领导权大的一方。然而不管哪种决策模型,其供应链利润均小于集中决策下的情形。     

供应中断和需求扰动下供应链竞合关系研究

考虑供应中断和需求扰动情境下2个供应商和1个零售商组成的两级供应链系统,构建了合作、静态非合作、嵌套式静态非合作3个博弈模型,分析集中式、分散式供应商竞争与合作情形下的零售商采购策略与供应商定价策略。研究表明,当市场需求增大时,分散式供应商合作情形下供应链整体利润最高;当市场需求减少时,集中式供应链整体利润最高。当权衡供应商订货成本与产品供应稳定性时,零售商倾向与相对稳定的供应商合作;当供需同时不确定时,仅较稳定的供应商受影响。     

系统动力学的碳排放政策对供应链影响

随着低碳经济的发展,碳排放政策对于供应链的影响越来越受到关注。建立了基于系统动力学的单个供应商和销售商的供应链模型,并在此基础上引入强制排放和碳税两种碳排放政策。利用模型仿真,分析两种排放政策对于供应商、销售商及整个供应链的总成本和碳排放的影响。研究表明在强制排放模型中,不同的碳排放额度会使销售商选择不同的订货周期,发现合理的排放额度才能引导供应链双方降低排放,否则不仅达不到减排的目的,反而影响供应链效率;而在碳税模型中,提高碳税税率虽然会使政府获取一定的收益,但是实际上可能带来供应链总成本的上升和碳排放的增加,需要合理制定碳税税率引导绿色供应链发展。     

存货影响销售量的两阶段供应链的VMI协调

研究在VMI环境下存货影响销售量的单供应商、单零售商的两阶段供应链的协调问题。建立了集中决策下的供应链模型,求出了整体供应链的利润函数;在分散决策下,采用收益共享契约对供应链进行协调,按Stackelberg博弈方式进行建模分析,发现收益共享契约无法协调供应链,即在利益分配上,与供应商相比,零售商获得了更多的供应链收益,而且分散式系统的收益始终低于集中决策下的水平;采用Nash协商对VMI供应链进行协调,完成了供应商和零售商收益的帕累托改进,不仅实现供应链的协调,而且达到了集中决策下的水平,最后通过算例进行了验证。     

Optimal batch ordering policies for assembly systems with guaranteed service

For a supply chain modelled as a multi-echelon inventory system, effective management of its inventory at each stock is critical to reduce inventory costs while assuring a given service level to customers. In our previous work, we used the guaranteed-service approach (GSA) to design optimal echelon batch ordering policies for continuous-review serial systems with Poisson customer demand and fixed order costs. The approach assumes that the final customer demand is bounded and each stock has a guaranteed service time in the sense that the demand of its downstream stock can always be satisfied in the service time. This paper extends this work by considering more general assembly systems. We first derive an analytical expression for the total cost of the system in the long run. The problem of finding optimal echelon batch ordering policies for the system can then be decomposed into two independent sub-problems: order size decision sub-problem and reorder point decision sub-problem. We develop efficient dynamic programming algorithms for the two sub-problems. Numerical experiments on randomly generated instances show the effectiveness of the proposed approach.     

三级短生命周期产品供应链退货协调研究

以由一个制造商、一个分销商和一个零售商构成的三级供应链为对象,研究退货契约在供应链协调中的应用.首先对集中控制情况下的决策进行分析,得出了整个供应链系统的最优生产量.然后分析了分散控制下参与成员的订购量和利润,以及供应链的总体利润,在此基础上建立了基于退货契约的供应链协调模型.研究得出对三级供应链实行退货契约不仅增加供...     

The supplier–buyer integrated production-inventory model with random yield

This paper revisits the traditional supplier–buyer integrated production-inventory model which deals with the problem of a manufacturer (supplier) supplying a product to a retailer (buyer) serving the consumer market with constant stationary demand. The product is manufactured in batches at a finite rate. The supplier's production batch is depleted by the buyer's replenishment orders at periodic intervals. The buyer's inventory is then consumed by the market demand at a fixed rate. The problem is the simultaneous computation of the manufacturer's production lot-size and the buyer's replenishment order quantity, i.e. the integrated production-inventory policy parameters. The key characteristic considered in this paper is that the manufacturing process is imperfect, and, hence, there are defective items in each production lot. As a result, each replenishment order shipped to the buyer includes defective products and the non-defective percentage in each such shipment is random. Considering the case where the supplier replenishes the buyer via equal-sized shipments, we develop an analytical expression of the total expected cost for the supplier–buyer system under consideration, with and without a considerable inspection time. We first examine the case where the inspection time is negligible, and then we present a generalisation to consider the inspection time explicitly. Our goal is to model the impact of random yield on the system performance. Our findings are useful for computing the integrated production-inventory policy parameters while considering the supply uncertainty due to an imperfect manufacturing process. Through numerical examples, we quantify the impact of supply with random yield on the system performance and illustrate its relationship with the demand and production rate.     

An analysis of warehouse and distribution strategies

We consider a case where seven retailers, all belonging to the same organization, order independently from the manufacturer. The organization wants to evaluate the advantage of creating a centralized warehouse facility. However, the investment costs for such a warehouse are considerable and the organization is thus cautious that any cost savings must outweigh the investment cost. The multi-echelon inventory control literature does not indicate when a centralized warehouse is clearly the best option. However, there is evidence that a centralized warehouse may be advantageous for low demand items which are expensive, as opposed to inexpensive fast moving items. Also the costs of the additional warehouse (i.e., capital investment and operating costs) play an important role. Hence, whether or not a warehouse can reduce overall cost depends heavily on the additional cost of the centralized warehouse. In order to keep the investment cost low we consider an alternative to the centralized warehouse, called virtual centralized warehousing. In the latter system no additional investment costs are necessary (i.e., the existing retailers have excess capacity at their current facilities) and the benefits of central warehousing are achieved.     

考虑批量订货成本的最优JIT订货与生产策略

由于增大单次订单量会降低企业订货灵活性,为此引入批量订货成本来衡量采购商从下达订单到收货期间所面临的与订货批量相关的风险成本。采购商通过综合权衡订货成本、运输成本、库存成本以及批量订货成本,从而得出合理的最优订货批量。基于由采购商和供应商组成的供应链,首先在JIT批量分解模式下,研究考虑批量订货成本后,集中式决策和分散式决策下的最优订货和生产策略。由于分散式决策下一方利益最大化时的最优决策常常是另一方无法接受的,进而分析了上下游企业间的不同议价能力,给出了双方均可接受的订货与生产策略。     

外包情境下品牌商主导的绿色供应链减排决策分析

针对外包情境下品牌商主导的绿色供应链,考虑产品全外包与制造外包两种情境,分别构建集中式决策、分散式决策博弈模型,得到各主体相应的最优决策。研究结果表明,无论是全外包还是制造外包情境下,相比分散式决策,集中式决策时的碳减排水平更高;同时,无论采取何种决策方式,全外包情境下能达到更高的碳减排水平。通过数值分析探讨碳减排成本系数和碳回扣系数对最优订购量、碳排放总量以及供应链利润的影响。     

时间敏感需求下的制造供应链研发协调研究

考虑由一个总装制造商和一个零部件供应商组成的制造供应链,在分别分析了集中系统和分散系统的研发决策的基础上,提出了研发费用分担机制,用博弈论的方法分析了供应商的研发投入决策和制造商的分担政策,探讨了博弈均衡存在的条件和供应链的系统协调性,得出了供应链Pareto有效研发合作方案。研究发现,研发费用分担机制可以刺激研发投入增加,不仅使供应链的利润得到优化,而且可以实现双赢;但这种激励还不足以使研发投入达到最优水平,不能实现供应链的Pareto最优。最后的赋值分析验证了理论分析得到的结论。     

回购与缺货成本下的连续时间报童模型

对带回购策略与缺货成本的连续时间报童模型,研究了其最优订购策略与批发价策略,使得生产商和零售商期望收益最大化。在零售价格依赖需求过程与零售价格外生的两种情形下,讨论了带回购策略和缺货成本对连续时间报童均衡策略的共同影响。运用随机最大值原理研究了以上问题均衡策略的存在唯一性,讨论了均衡策略满足的条件,在价格外生情形下得出结论：回购策略与缺货成本的共同作用,使得零售商的最优订购量和供应商的最优批发价格均提高很多。最后,通过数值算例做了最优批发价格与最优订购策略的敏感度分析,具体例子验证了已得结论。     

An improved ordering policy for continuous review inventory systems with arbitrary inter-demand time distributions

In this paper, we revisit the optimality of (s,S) policies in continuous review inventory models where demand forms a renewal process. We explain why when orders are placed at demand epochs, (s,S) policies are not optimal in general, and propose a simple but practical ordering policy by introducing a delay in order placement as a policy parameter. Under our proposed policy, the operating characteristics of such systems can be evaluated using the existing results in the literature. In order to demonstrate the effectiveness of our policy, we restrict our analysis to a special class of inventory systems where demand follows a counting process, fixed ordering costs are negligible and leadtimes are constant. We derive expressions for the operating characteristics of such systems under our policy and present insights on the behavior of the policy parameters which minimize the average total cost rate under our policy. Using these results, we develop an efficient heuristic for computing the policy parameters. Finally, we investigate the effectiveness of our policy in comparison to policies which place orders only at demand epochs. The results of our numerical experiment indicate that our policy can result in a significant savings.