Managing an integrated production inventory system with information on the production and demand status and multiple non-unitary demand classes

In this paper, we study a system consisting of a manufacturer or supplier serving several retailers or clients. The manufacturer produces a standard product in a make-to-stock fashion in anticipation of orders emanating from n retailers with different contractual agreements hence ranked/prioritized according to their importance. Orders from the retailers are non-unitary and have sizes that follow a discrete distribution. The total production time is assumed to follow a k₀-Erlang distribution. Order inter-arrival time for class l demand is assumed to follow a k_l-Erlang distribution. Work-in-process as well as the finished product incur a, per unit per unit of time, carrying cost. Unsatisfied units from an order from a particular demand class are assumed lost and incur a class specific lost sale cost. The objective is to determine the optimal production and inventory allocation policies so as to minimize the expected total (discounted or average) cost. We formulate the problem as a Markov decision process and show that the optimal production policy is of the base-stock type with base-stock levels non-decreasing in the demand stages. We also show that the optimal inventory allocation policy is a rationing policy with rationing levels non-decreasing in the demand stages. We also study several important special cases and provide, through numerical experiments, managerial insights including the effect of the different sources of variability on the operating cost and the benefits of such contracts as Vendor Managed Inventory or Collaborative Planning, Forecasting, and Replenishment. Also, we show that a heuristic that ignores the dependence of the base-stock and rationing levels on the demands stages can perform very poorly compared to the optimal policy.     

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 collaborative decentralized distribution system with demand forecast updates

In this paper, we study inventory pooling coalitions within a decentralized distribution system consisting of a manufacturer, a warehouse (or an integration center), and n retailers. At the time their orders are placed, the retailers know their demand distribution but do not know the exact value of the demand. After certain production and transportation lead time elapses, the orders arrive at the warehouse. During this time, the retailers can update their demand forecasts.We first focus on cooperation among the retailers - the retailers coordinate their initial orders and can reallocate their orders in the warehouse after they receive more information about their demand and update their demand forecasts. We study two types of cooperation: forecast sharing and joint forecasting. By using an example, we illustrate how forecast sharing collaboration might worsen performance, and asymmetric forecasting capabilities of the retailers might harm the cooperation. However, this does not happen if the retailers possess symmetric forecasting capabilities or they cooperate by joint forecasting, and the associated cooperative games have non-empty cores.Finally, we analyze the impact that cooperation and non-cooperation of the retailers has on the manufacturer’s profit. We focus on coordination of the entire supply chain through a three-parameter buyback contract. We show that our three-parameter contract can coordinate the system if the retailers have symmetric margins. Moreover, under such a contract the manufacturer benefits from retailers’ cooperation since he can get a share of improved performance.     

A two-level supply chain with partial backordering and approximated Poisson demand

We consider a two-level supply chain with a number of identical, independent ‘retailers’ at the lower echelon and a single supplier at the upper echelon controlled by continuous review inventory policy (R, Q). Each retailer experiences Poisson demand with constant transportation times. We assume constant lead time for replenishing supplier orders from an external warehouse to the supplier and unsatisfied retailer orders are backordered in the supplier. We assume that the unsatisfied demand is partially backordered in the identical retailers. The partially backordering policy is implemented in the identical retailers using an explicit control parameter ‘b’ which limits the maximum number of backorders allowed to be accumulated during the lead time. We develop an approximate cost function to find optimal reorder points for given batch sizes in all installations, the optimal value of b in the identical retailers and the related accuracy is assessed through simulation.     

Uniform distribution of inventory positions in two-echelon periodic review systems with batch-ordering policies and interdependent demands

We consider a two-level inventory system in which there are one supplier and multiple retailers. The retailers face stochastic, interdependent customer demands. Each location employs a periodic-review (R,nQ), or lot-size reorder point, inventory policy. We show that each location's inventory positions are stationary and the stationary distribution is uniform and independent of any other's.     

A two-echelon base-stock inventory model with Poisson demand and the sequential processing of orders at the upper echelon

We consider a two-echelon inventory system with a number of non-identical, independent ‘retailers’ at the lower echelon and a single ‘supplier’ at the upper echelon. Each retailer experiences Poisson demand and operates a base stock policy with backorders. The supplier manufactures to order and holds no stock. Orders are produced, in first-come first-served sequence, with a fixed production time. The supplier therefore functions as an M/D/1 queue. We are interested in the performance characteristics (average inventory, average backorder level) at each retailer. By finding the distribution of order lead time and hence the distribution of demand during order lead time, we find the steady state inventory and backorder levels based on the assumption that order lead times are independent of demand during order lead time at a retailer. We also propose two alternative approximation procedures based on assumed forms for the order lead time distribution. Finally we provide a derivation of the steady state inventory and backorder levels which will be exact as long as there is no transportation time on orders between the supplier and retailers. A numerical comparison is made between the exact and approximate measures. We conclude by recommending an approach which is intuitive and computationally straightforward.     

Coordinating ordering and pricing decisions in a two-stage distribution system with price-sensitive demand through short-term discounting

We consider a short-term discounting model in which the distributor offers a discounted price for the retailers’ orders placed at the beginning of its replenishment cycle, in a non-cooperative distribution system with one distributor and multiple retailers, each facing price-sensitive demand. We examine the value of the price discount strategy as a mechanism for the distributor to coordinate the retailers’ ordering and pricing decisions under two common types of demand, linear demand in price and constant elasticity demand in price. Our numerical study reveals that, in the presence of homogeneous retailers (namely, retailers with identical demand rates), the distributor’s profit improvement due to coordination generally decreases as the number of retailers or the inventory holding cost rate increases, but increases as price elasticity increases. Although an increase in the inventory holding cost rate has a negative effect on the distributor’s profit, it may have a positive effect on the retailers’ profits. We further find that with heterogeneous retailers (namely, retailers with different demand rates), offering a discounted price under linear demand benefits the distributor when both the inventory holding cost rate and the variation in demand are either small or large. This cross effect, however, is absent under constant elasticity demand.     

Optimal production and inventory rationing policies with selective-information sharing and two demand classes

This paper studies the impact of partner selection on the value of information sharing in a distribution system with one capacitated make-to-stock manufacturer and two retailers. When the high priority retailer with a higher shortfall cost is the sole partner, in the case that the low priority one places an order, the manufacturer allocates inventory more accurately according to more predictable orders from the high priority retailer. When only the low priority retailer shares information, the manufacturer is better informed about orders from this retailer, which shall trigger rationing decisions. Such intriguing differences in utilizing information from two prioritized retailers further induce different interactions between production and rationing policies and form two distinctive but closely related selective-information sharing systems. We characterize the manufacturer’s optimal production and rationing policies under both systems. Through a numerical study, we emphasize the effectiveness of partnering with the high priority retailer. When the manufacturer can establish information sharing links with only one retailer, such a choice usually brings more benefits despite differences in order sizes and/or demand rates of the two retailers. When a selective-information sharing system is the pilot run to full-information sharing, we find that the value of information throughout the implementation process often exhibits second-mover advantage and such a choice also helps the manufacturer create a more balanced return pattern. Finally, we illustrate that the cost-effectiveness of inventory rationing can be significant and optimally rationing inventory is the prerequisite for the superior of the selective-information sharing system with the high priority retailer.     

选址-库存-路径问题模型及其集成优化算法

设施选址、库存控制和车辆路径安排是物流系统优化中的三个关键问题,三者之间存在相互依赖的关系,应该根据这种关系来相应地进行综合优化与管理物流活动。以典型的单一生产基地、单一产品、采用不断审查的(Q, r)库存策略的供应链二级分销网络为研究对象,建立了一个随机型选址-库存-路径问题优化模型;在将非线性混合整数规划转化为线性整数集合覆盖模型的基础上,采用列生成算法来获得一个近似最优解,再用分支定价法对初始解进行改进,以实现对整个问题“完全集成”的优化。最后,用随机生成的方式,产生了10至160个客户的计算实例,分析了运输费用和库存费用对总成本的影响,算法运算时间表明本文给出的算法能较快地求解这一复杂问题。     

风险时收益共享-贸易信贷契约下多个竞争零售商的供应链协调

在供应商向多个零售商提供贸易信贷的环境下,本文考虑了零售商存在违约风险和他们之间存在竞争时的供应链协调问题。研究表明,在比例分配市场需求下,多个竞争的零售商之间存在唯一的纳什均衡订购量,以及零售商违约风险的提高和他们之间竞争增强都会增加均衡订购量。当零售商之间的竞争较弱时,贸易信贷将无法协调供应链。为此,本文使用了收益分享与贸易信贷相结合的机制以协调供应链,且分析了零售商的违约风险和他们之间的竞争对协调契约参数的影响。当零售商的竞争强度一定时,批发价和风险溢价都随着零售商违约风险的提高而增大,而收益分享比例随着违约风险的提高而减小;当零售商的违约风险一定时,批发价和风险溢价都随着零售商之间竞争强度的提高而增大,而收益分享比例随着竞争强度的增强而减小。进一步的研究发现,零售商的违约风险越高以及他们之间竞争越激烈对零售商越不利,而对供应商越有利。最后,结合数值实验验证了收益共享-贸易信贷契约的有效性。     

分销供应链中竞争零售商联盟的稳定性

针对由单一供应商和三个相互竞争零售商组成的两层分销供应链系统,在三种不同的博弈框架下,采用合作博弈论中短视的Nash稳定性概念与远视的最大一致集(LCS)概念研究了供应商与不同零售商联盟间的定价博弈,分别讨论了不同类型零售商联盟的稳定性。发现不论是在供应商处于领导地位,还是在零售商处于领导地位的市场中,当竞争强度较弱时,大联盟不是短视零售商联盟的稳定结构,却有可能是远视零售商联盟的稳定结构;当竞争强度较强时,则无论是短视零售商还是远视零售商都以大联盟为稳定结构,但是,在供应商处于领导地位的市场中,远视零售商形成大联盟的阈值较高;在供应商和零售商地位相同的市场中,大联盟则是远视零售商和短视零售商共同的稳定结构。     

Game Theoretic Analysis of a Distribution System with Customer Market Search

Consider a distribution system with one supplier and two retailers. When a stockout occurs at one retailer customers may go to the other retailer. We study a single period model in which the supplier may have infinite or finite capacity. In the latter case, if the total quantity ordered (claimed) by the retailers exceeds the supplier’s capacity, an allocation policy is involved to assign the limited capacity to the retailers. We analyze the inventory control decisions for the retailers using a game theoretical approach. The necessary and sufficient conditions are derived for the existence of a unique Nash equilibrium. A computational procedure is also proposed to calculate the Nash equilibrium. In case the Nash equilibrium does not exist, we use the concept of Stackelberg game to develop optimal strategies for both the leader and the follower. The work was partially supported by the National Textile Center of the US Department of Commerce under Grant No. I01-S01. The second author is supported in part by NSF under DMI-0196084 and DMI-0200306.     

Order splitting in single sourcing with scheduled-release orders

Traditional inventory models assume that a buyer places one order with a supplier in each order cycle. A large number of researchers have studied the benefits of dual sourcing such that an order quantity is split and placed simultaneously with two suppliers. We show that many of the benefits of dual sourcing are due to order splitting rather than using two suppliers. We investigate order splitting with one supplier such that the first part of the order is sent out immediately but the second part of the order is released later (scheduled-release). Through extensive computational results, we show that in many situations where dual sourcing or the use of a cheaper supplier would be cost effective, single sourcing with order splitting using scheduled-release orders is better. The paper provides a quantitative rationale to continue with one supplier. We also summarize the qualitative reasons to prefer single sourcing or multiple sourcing.     

Supplier–manufacturer coordination in capacitated two-stage supply chains

Manufacture-to-order is an increasingly popular strategy in commodity electronics and other similar markets where many different product configurations can be produced from common components. To succeed in this environment, manufacturers need to keep both cost and order fulfillment time low. In this article, we compare three different mechanisms that a manufacturer, whose revenues depend on order delays, may use to affect its component supplier’s inventory decisions. These mechanisms are specifying components inventory level, offering a share of the earned revenues to the supplier (called simple revenue sharing), and offering a two-part revenue-sharing scheme. We show that whereas the first two approaches do not lead to supply chain coordination, the two-part scheme does. We demonstrate with numerical experiments that up to a point, the component supplier benefits from having a high utilization of its production facility, whereas the manufacturer benefits from having excess production capacity.     

Production-inventory systems in stochastic environment and stochastic lead times

We consider a production-inventory system where the production and demand rates are modulated by a finite state Continuous Time Markov Chain (CTMC). When the inventory position (inventory on hand – backorders+inventory on order) falls to a reorder point r, we place an order of size q from an external supplier. We consider the case of stochastic leadtimes, where the leadtimes are i.i.d. exponential(μ) random variables, and orders may or may not be allowed to cross. We derive the distribution of the inventory level, and analyze the long run holding, backlogging, and ordering cost rate per unit time. We use simulation to study the sensitivity of the system to the distribution of the lead times.     

Wholesale-price contract of supply chain with information gathering

This paper investigates a wholesale-price contract of supply chain under the endogenous information structure. This supply chain consists of one supplier and one retailer during the selling season. The retailer does not know his selling cost but can spend resources to acquire information. The supplier offers a contract, which induces the retailer to gather information and generate more production orders with beta costs. We find that there exists an upper bound of the information gathering cost such that the supplier induces the retailer to gather information. The increasing cost of information gathering may decrease the order quantity and wholesale price. Moreover, the cost beta has an impact on the expected profits of the two parties. With the increasing cost of information gathering, the supplier’s expected profit is reduced, while that of the retailer becomes ambiguous in terms of the distribution function and the interval of selling cost information. Finally, a numerical example is presented to explain the main results.     

Replenishment routing problems between a single supplier and multiple retailers with direct delivery

We consider the replenishment routing problems of one supplier who can replenish only one of multiple retailers per period, while different retailers need different periodical replenishment. For simple cases satisfying certain conditions, we obtain the simple routing by which the supplier can replenish each retailer periodically so that shortage will not occur. For complicated cases, using number theory, especially the Chinese remainder theorem, we present an algorithm to calculate a feasible routing so that the supplier can replenish the selected retailers on the selected periods without shortages.     

需求依赖于货架展示量的单供应商两零售商模型与协调合同设计

针对一个供应商和两个竞争的零售商组成的单产品供应链,研究零售商的货架展示量和订货决策及供应链协调问题.假定产品总需求随机依赖于两个零售商的总货架展示量,给出了每个零售商的产品需求,然后分别建立了供应链的集中式决策模型和分散式决策模型,提出了协调供应链的回购加线性补贴合同和回购加货架补贴加转移支付合同,最后的算例表明了决策模型和协调合同的有效性.     

Multi-location transshipment problem with capacitated production

We consider coordination among stocking locations through replenishment strategies that explicitly take into account lateral transshipments, i.e., transfer of a product among locations at the same echelon level. Our basic contribution is the incorporation of supply capacity into the traditional transshipment model. Our goal is to analyze the impact on system behavior and on stocking locations’ performance of the fact that the supplier may fail to fulfill all the replenishment orders. We therefore formulate the capacitated supply scenario as a network flow problem embedded in a stochastic optimization problem, which is solved through a sample average approximation method. We find that, depending on the production capacity, system behavior can vary drastically. Moreover, in a production-inventory system, we find evidence that either capacity flexibility (i.e., extra production) or transshipment flexibility (i.e., pooling) is required to maintain a desired level of service.     

Logistics distribution network design with two commodity categories

In this paper, we study the design of a logistics distribution network consisting of a supplier, a set of potential warehouses, and a set of retailers. There are commodities from two product categories, that is, category A and category B, flowing across the network. The demand for commodities in product category A is stable. The demand for commodities in product category B is highly uncertain. We show that the network design problem to distribute the commodities in both product categories can be formulated as the uncapacitated facility location problem with monotone submodular costs and tackled using a cutting plane algorithm. We propose a strongly polynomial time algorithm for the nonlinear discrete optimization problem, which must be solved in each iteration of the cutting plane algorithm. We also provide the computational results, and summarize the insights based on the proposed model and the solution algorithm.