基于库存分担策略的装配系统准时供货模型研究

本文考虑一个由多供应商和单制造商构成的装配系统。当市场的需求时间无法确定时,制造商通过对供应商设定合理的库存分担策略来降低自身成本,供应商则需要自行决定对制造商的补货时间并承担相应的库存持有成本和延迟惩罚成本。文章同时建立了供应商之间的纳什博弈模型和以制造商为主方的主从博弈模型,以找到供应商的最佳供货时间和制造商最优的库存承担时限。通过对比不同模式下供应链的整体绩效,找到实现供应链协调运作的必要条件,并通过数据分析进一步证明相关结论。     

一类供应商管理库存供应链协调策略研究

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供应链模型.然后,分别分析分散式、集中式和VMI三种供应链模式下的库存补充数量最优解及各方收益情况,得到VMI的实施将可能造成供应商收益下降.再运用委托-代理理论分别讨论了信息对称和信息不对称时的VMI数量折扣契约设计问题.最后,给出算例说明了,此协调策略有助于VMI的实施.     

库存成本变化的VMI供应链协调

提出了库存成本变化的经济订货批量(EOQ)模型，基于该模型研究了库存成本变化时供应商管理库存(VMI)系统的最优协议问题。在该系统中，订货商和供应商达成缺货成本共担协议：当缺货发生时，供应商需要向订货商支付缺货补偿。订货商和供应商分散决策，订货商通过设计协议来减少其成本，而供应商通过制定补货决策来缩小自身成本。通过与传统系统和整合系统的比较，得出了库存成本变化时VMI系统的最优补货决策和缺货成本共担协议。采用数值算例验证了分析结果。结果表明，当且仅当供应商预期成本等于整合系统的最小总成本与固定缺货罚金之和时，VMI系统与整合系统具有相同的补货决策和系统绩效，即能够实现供应链协调。     

Replenishment Policies for Multi‐Product Stochastic Inventory Systems with Correlated Demand and Joint‐Replenishment Costs

This study analyzes optimal replenishment policies that minimize expected discounted cost of multi‐product stochastic inventory systems. The distinguishing feature of the multi‐product inventory system that we analyze is the existence of correlated demand and joint‐replenishment costs across multiple products. Our objective is to understand the structure of the optimal policy and use this structure to construct a heuristic method that can solve problems set in real‐world sizes/dimensions. Using an MDP formulation we first compute the optimal policy. The optimal policy can only be computed for problems with a small number of product types due to the curse of dimensionality. Hence, using the insight gained from the optimal policy, we propose a class of policies that captures the impact of demand correlation on the structure of the optimal policy. We call this class (s, c, d, S)‐policies, and also develop an algorithm to compute good policies in this class, for large multi‐product problems. Finally using an exhaustive set of computational examples we show that policies in this class very closely approximate the optimal policy and can outperform policies analyzed in prior literature which assume independent demand. We have also included examples that illustrate performance under the average cost objective.     

VMI环境下库存竞争性产品的补货策略及最优货架空间的确定

本文在文献[1]的研究基础上,通过深入剖析FKO模型,运用动态规划方法,探讨了呈现特殊需求性质的库存竞争性产品在VMI环境下的多期动态补货策略,以及传统库存管理中不加考虑的库存空间优化问题。本文一方面是对FKO模型的补充与扩展,同时也证实了对于在特定的VMI补货环境下采用多期库存盘查模式的供应商来说,封顶式的补货策略是最优的,并且其关于最优补货水平的多期决策都是无远见的。因此收益分享合同下的单期最优库存水平可以作为设定最优货架展示空间的依据。     

物流联合外包下库存管理模式对供应链运作的影响

针对由供应商、第三方物流服务商和零售商组成的供应链,考虑供需双方将物流服务联合外包给第三方物流服务商、共同承担运费的情形,探究供应商管理库存和寄售库存两类库存管理模式的引入对供应链运作及合同设计的影响。分别在传统的零售商管理库存、仅引入寄售库存的零售商管理寄售库存以及同时引入供应商管理库存和寄售库存的供应商管理寄售库存三种模式下,构建了第三方物流服务商主导、供应商和零售商跟随的序贯非合作博弈模型,证明了所有模式下均衡的订购量/寄售量均存在且唯一,并探讨了均衡结果随零售商运费分摊比例、转移支付价格两个关键参数的变化。横向对比三种模式下的均衡结果和集中决策下的最优结果,发现：零售商管理库存模式下的均衡订购量总是低于零售商管理寄售库存模式以及集中决策下的结果,而其他库存管理模式下的订购量并非一定低于集中决策下的结果;不同库存管理模式下,均衡状态下的订购量/寄售量及供应链总的期望收益大小关系取决于供应商和零售商的类边际(毛利)贡献率,从而表明,供应链环境下,上下游成员企业的收益结构、盈利水平等对于库存决策及库存模式的选取有重要影响。此外,在绝大多数情形下,不同库存管理模式下的均衡订购量与集中决...     

The value of VMI beyond information sharing in a single supplier multiple retailers supply chain under a non-stationary (Rn,Sn) policy

This study aims to determine the value of vendor-managed inventory (VMI) over independent decision making with information sharing (IS) under non-stationary stochastic demand with service-level constraints. For this purpose, we utilize mixed-integer linear programming formulations to quantify the benefits that can be accrued by a supplier, multiple retailers and the system as a whole by switching from IS to VMI. More specifically, we investigate the incremental value that VMI provides beyond IS in terms of expected cost savings, inventory reductions, and decrease in shipment sizes from the supplier to the retailers by conducting a large number of computational experiments. Results reveal that the decision transfer component of VMI improves these performance measures significantly when the supplier׳s setup cost is low and order issuing efficiency is high. The benefits offered by VMI are negligible under the problem settings where the supplier׳s order issuing efficiency is low and the production setup serves solely a single replenishment under IS.     

确定需求下VMI-TPL分销供应链集成库存策略研究

针对VMI在实施中存在的问题,本文将TPL引入VMI,构建了确定需求下,由制造商、TPL和多零售商构成,考虑原材料、产成品的VMI-TPL供应链集成库存模型,并给出了最优生产策略和库存策略.在此基础上,文章进一步讨论了产需比等变量对供应链成本的影响,并比较分析了引入TPL前后VMI的最优策略.研究表明:引入TPL能有效降低供应链平均总成本,避免制造商高库存成本和高运营风险;制造商的产需比(p/d)对TPL引入后的效果影响很大,产需比越大,引入TPL的效果越好.     

Hedging strategic flexibility in the distribution optimization problem

Motivated by the increasing prevalence of flexibility hedging in corporate-level risk management programs, this paper focuses on the treatment of hedging operational risks in the coordinated replenishment and shipment for distribution systems. The forward option pricing model with the generalized autoregressive conditional heteroskedasticity (GARCH) model for stochastic demand forecasting is adopted for constructing inventory volume flexibility. We therefore propose a hedge-based coordinated inventory replenishment and shipment (HCIRS) methodology for flexibly making inventory hedging and optimal routing assignment decisions as well as coordinating replenishment and shipment policies. The HCIRS methodology provides insight into strategic flexibility adopted for a real-life inventory–distribution problem faced by one of the major East Asia food supply networks and turns out to be very efficient. The proposed HCIRS methodology has provided evidence of better results than the traditional operational techniques for the presented case in this paper.     

供应链库存协调策略研究

研究和分析了直运型供应链通过共同补给期协调库存的策略问题。在该供应链中,单一供应商提供单一产品给面临随机需求的单一零售商。在所提出的库存协调策略条件下,供应商指定共同补给期,当零售商按供应商指定的共同补给期作为其订货周期时,供应商提供零售商一定的价格折扣。这种协调策略可以视为Stackelberg博弈。在阐述了解决该博弈问题的方法后,进行了数值实验,分析了采用这种协调策略的利益。     

基于VMI理论的南水北调水资源供应链的库存协调

节点湖泊水资源库存的协调控制是南水北调工程运行管理中的重要研究内容之一.通过引入供应链的产品库存控制理论,以由长江抽水口和单个节点湖泊共同组成的简单南水北调水资源供应链为研究对象,分别建立了水资源库存集中决策、双方独立决策和VMI决策等情况下的湖泊水资源最优订货量模型和双方利润模型.在此基础上,提出了VMI策略下的水资源库存管理的转移支付协调策略,并给出了该协调策略的有效性,最后利用仿真算例对相关结论进行了验证和分析.     

The Effect of Distribution Processes on Replenishment Lead Time and Inventory

We investigate the interrelationship of distribution center picking policies and supply chain inventory performance. In particular, we show how the picking sequence in the upstream supply chain link affects the inventory levels of items being replenished to a downstream link for a common “ship‐when‐full” trailer dispatching policy. Perturbing the picking sequence affects items’ inventory levels asymmetrically which causes the aggregate system inventory to vary. We separate the items in replenishment into those units in transit and those awaiting shipment from the upstream distribution step: we call the latter the residual replenishment. We show that the process governing aggregate residual replenishment is Markov and has a stationary distribution that is discrete uniform. Computing the item‐level residual distribution is intractable and so we develop analytical models from which we derive hypotheses for the effectiveness of stable vs. random picking sequences, how item residual replenishment varies with stable picking sequences, and how the aggregate inventory level changes with picking sequence. These suggest a heuristic sequencing algorithm for minimizing inventory, which performs well in simulation tests over a large testbed of parameter sets.     

Point‐of‐Use Hybrid Inventory Policy for Hospitals

Modern point‐of‐use technology at hospitals has enabled new replenishment policies for medical supplies. One of these new policies, which we call the hybrid policy, is currently in use at a large U.S. Midwest hospital. The hybrid policy combines a low‐cost periodic replenishment epoch with a high‐cost continuous replenishment option to avoid costly stockouts. We study this new hybrid policy under deterministic and stochastic demand. We develop a parameter search engine using simulation to optimize the long‐run average cost per unit time and, via a computational study, we provide insights on the benefits (reduction in cost, inventory, and number of replenishments) that hospitals may obtain by using the hybrid policy instead of the commonly used periodic policies. We also use the optimal hybrid policy parameters from the deterministic analysis to propose approximate expressions for the stochastic hybrid policy parameters that can be easily used by hospital management.      

供需不确定下基于MOI和VMI模式的供应链协同比较研究

为分析供应链运作机制对降低随机供应商产出和随机需求的影响,对比研究了两供应商-单制造商系统在MOI和VMI两种模式下的供应链协同模型。MOI模式下,制造商管理并持有库存,提出了供应风险共享的协同机制;VMI模式下,供应商管理并持有库存,提出了收益共享与额外惩罚的协同机制。分析了集中决策、MOI和VMI模式下的最优批量决策,证明了VMI模式下存在唯一的纳什均衡。研究还发现,VMI模式更容易协调供应链,有效降低供需不确定的影响。MOI模式下的供应链可实现帕累托改进,但不能实现协调;而当参数满足一定关系时,VMI模式下供应链的期望利润可达到集中决策。     

基于CPFR的多产品分销系统库存优化模型

本文中的分销系统由生产多种产品的多个制造商,一个地区分销中心DC,多个零售商所组成,系统采用基于CPFR来确定订货临界点,并且在假设DC和零售商都实行连续性盘点的(R,Q)库存控制策略,提前期为随机变量,零售商需求为泊松分布的前提下,以整个分销系统的库存成本最小化为目标函数,以DC和零售商的多产品服务水平为约束条件,通过确定最佳订货批量,建立了此多产品分销系统的库存优化模型,从而达到有效控制库存的目的.     

Order Progress Information: Improved Dynamic Emergency Ordering Policies

Technologies such as radio‐frequency identification and global positioning systems can provide improved real‐time tracking information for products and replenishment orders along the supply chain. We call this type of visibility order progress information. In this paper, we investigate how order progress information can be used to improve inventory replenishment decisions. To this end, we examine a retailer facing a stochastic lead time for order fulfillment. We characterize a replenishment policy that is based on the classical (Q, R) policy and that allows for releasing emergency orders in response to the order progress information. We show that the optimal structure of this policy is given by a sequence of threshold values dependent on order progress information. In a numerical study we evaluate the cost savings due to this improved replenishment policy.     

Managing Slow‐Moving Perishables in the Grocery Industry

We address the value of information and value of centralized control in the context of a two‐echelon, serial supply chain with one retailer and one supplier that provide a single perishable product to consumers. Our analysis is relevant for managing slow‐moving perishable products with fixed lot sizes and expiration dates of a week or less. We evaluate two supply chain structures. In the first structure, referred to as decentralized information sharing, the retailer shares its demand, inventory, and ordering policy with the supplier, yet both facilities make their own profit‐maximizing replenishment decisions. In the second structure, centralized control, incentives are aligned and the replenishment decisions are coordinated. The latter supply chain structure corresponds to the industry practices of company‐owned stores or vendor‐managed inventory. We measure the value of information and value of centralized control as the marginal improvement in expected profits that a supply chain achieves relative to the case when no information is shared and decision making is decentralized. Key assumptions of our model include stochastic demand, lost sales, and fixed order quantities. We establish the importance of information sharing and centralized control in the supply chain and identify conditions under which benefits are realized. As opposed to previous work on the value of information, the major benefit in our setting is driven by the supplier's ability to provide the retailer with fresher product. By isolating the benefit by firm, we show that sharing information is not always Pareto‐improving for both supply chain partners in the decentralized setting.     

考虑产品变质的VMI混合补货发货策略及优化仿真

本文研究了“产品可变质”情况下的VMI库存补货与装运调度问题,并建立了Poisson需求过程下的VMI混合补货发货模型,根据此模型通过简单的规划求解即可得到使长期平均成本最小的最佳混合策略组合。由于模型推演过程中涉及到对补货周期内期望发货次数的近似估计,因而模型解是拟最优的。算例和模型仿真显示,模型结果与仿真结果十分相近,从而模型有效性得以确认。     

Managing Retail Shelf and Backroom Inventories When Demand Depends on the Shelf‐Stock Level

Inventory displayed on the retail sales floor not only performs the classical supply function but also plays a role in affecting consumers’ buying behavior and hence the total demand. Empirical evidence from the retail industry shows that for some types of products, higher levels of on‐shelf inventory have a demand‐increasing effect (“billboard effect”) while for some other types of products, higher levels of on‐shelf inventory have a demand‐decreasing effect (“scarcity effect”). This suggests that retailers may use the amount of shelf stock on display as a tool to influence demand and operate a store backroom to hold the inventory of items not displayed on the shelves, introducing the need for efficient management of the backroom and on‐shelf inventories. The purpose of this study is to address such an issue by considering a periodic‐review inventory system in which demand in each period is stochastic and depends on the amount of inventory displayed on the shelf. We first analyze the problem in a finite‐horizon setting and show under a general demand model that the system inventory is optimally replenished by a base‐stock policy and the shelf stock is controlled by two critical points representing the target levels to raise up/drop down the on‐shelf inventory level. In the infinite‐horizon setting, we find that the optimal policies simplify to stationary base‐stock type policies. Under the billboard effect, we further show that the optimal policy is monotone in the system states. Numerical experiments illustrate the value of smart backroom management strategy and show that significant profit gains can be obtained by jointly managing the backroom and on‐shelf inventories.     

基于系统动力学的库存管理研究

在讨论系统动力学相关理论及其应用现状的基础上,研究了供应商代管库存模式(VenderManagedInventory,VMI)的管理思想,并借助建模平台STELLAithink,建立了供应链环境下库存管理的系统动力学仿真模型,并对模型的运行和模拟结果进行了分析。