Multilocation Inventory Systems With Centralized Information.

The management of multi-echelon inventory systems has been both an important and challenging research area for many years. The rapid advance in information technology and the emphasis on integrated supply chain management have new implications for the successful operation of distribution systems. This research focuses on the study of some fundamental issues related to the operation of a multilocation inventory system with centralized information. First, we do a comparative analysis to evaluate the overall performance of individual versus centralized ordering policies for a multi-store distribution system where centralized information is available. This study integrates the existing research and clarifies one of the fundamental questions facing inventory managers today: whether or not ordering decisions should be centralized. Next, we consider a multi-store distribution system where emergency transshipments are permitted among these stores. Based on some simplifying assumptions, we develop an integrated model with a joint consideration of inventory and transshipment components. An approximately optimal (s, S) policy is obtained through a dynamic programming technique. This ordering policy is then compared with a simplified policy that assumes free and instantaneous transshipments. We also examine the relative performance of base stock policies for a centralized-ordering distribution system. Numerical studies are provided to give general guidelines for use of the policies

Inventory models with lateral transshipments : a review

Lateral transshipments within an inventory system are stock movements between locations of the same echelon. These transshipments can be conducted periodically at predetermined points in time to proactively redistribute stock, or they can be used reactively as a method of meeting demand which cannot be satised from stock on hand. The elements of an inventory system considered, e.g. size, cost structures and service level denition, all in uence the best method of transshipping. Models of many dierent systems have been considered. This paper provides a literature review which categorizes the research to date on lateral transshipments, so that these dierences can be understood and gaps within the literature can be identied

Virtual transshipments and revenue-sharing contracts in supply chain management

This dissertation presents the use of virtual transshipments and revenue-sharing contracts for inventory control in a small scale supply chain. The main objective is to maximize the total profit in a centralized supply chain or maximize the supply chain\u27s profit while keeping the individual components\u27 incentives in a decentralized supply chain. First, a centralized supply chain with two capacitated manufacturing plants situated in two distinct geographical regions is considered. Normally, demand in each region is mostly satisfied by the local plant. However, if the local plant is understocked while the remote one is overstocked, some of the newly generated demand can be assigned to be served by the more remote plant. The sources of the above virtual lateral transshipments, unlike the ones involved in real lateral transshipments, do not need to have nonnegative inventory levels throughout the transshipment process. Besides the theoretical analysis for this centralized supply chain, a computational study is conducted in detail to illustrate the ability of virtual lateral transshipments to reduce the total cost. The impacts of the parameters (unit holding cost, production cost, goodwill cost, etc.) on the cost savings that can be achieved by using the transshipment option are also assessed. Then, a supply chain with one supplier and one retailer is considered where a revenue-sharing contract is adopted. In this revenue-sharing contract, the retailer may obtain the product from the supplier at a less-than-production-cost price, but in exchange, the retailer must share the revenue with the supplier at a pre-set revenuesharing rate. The objective is to maximize the overall supply chain\u27s total profit while upholding the individual components\u27 incentives. A two-stage Stackelberg game is used for the analysis. In this game, one player is the leader and the other one is the follower. The analysis reveals that the party who keeps more than half of the revenue should also be the leader of the Stackelberg game. Furthermore, the adoption of a revenue-sharing contract in a supply chain with two suppliers and one retailer under a limited amount of available funds is analyzed. Using the revenue-sharing contract, the retailer pays a transfer cost rate of the production cost per unit when he obtains the items from the suppliers, and shares the revenue with the suppliers at a pre-set revenue-sharing rate. The two suppliers have different transfer cost rates and revenue-sharing rates. The retailer will earn more profit per unit with a higher transfer cost rate. How the retailer orders items from the two suppliers to maximize his expected profit under limited available funds is analyzed next. Conditions are shown under which the optimal way the retailer orders items from the two suppliers exists

Pooling and polling : creation of pooling in inventory and queueing models

The subject of the present monograph is the ‘Creation of Pooling in Inventory and Queueing Models’. This research consists of the study of sharing a scarce resource (such as inventory, server capacity, or production capacity) between multiple customer classes. This is called pooling, where the goal is to achieve cost or waiting time reductions. For the queueing and inventory models studied, both theoretical, scientific insights, are generated, as well as strategies which are applicable in practice. This monograph consists of two parts: pooling and polling. In both research streams, a scarce resource (inventory or server capacity, respectively production capacity) has to be shared between multiple users. In the first part of the thesis, pooling is applied to multi-location inventory models. It is studied how cost reduction can be achieved by the use of stock transfers between local warehouses, so-called lateral transshipments. In this way, stock is pooled between the warehouses. The setting is motivated by a spare parts inventory network, where critical components of technically advanced machines are kept on stock, to reduce down time durations. We create insights into the question when lateral transshipments lead to cost reductions, by studying several models. Firstly, a system with two stock points is studied, for which we completely characterize the structure of the optimal policy, using dynamic programming. For this, we formulate the model as a Markov decision process. We also derived conditions under which simple, easy to implement, policies are always optimal, such as a hold back policy and a complete pooling policy. Furthermore, we identified the parameter settings under which cost savings can be achieved. Secondly, we characterize the optimal policy structure for a multi-location model where only one stock point issues lateral transshipments, a so-called quick response warehouse. Thirdly, we apply the insights generated to the general multi-location model with lateral transshipments. We propose the use of a hold back policy, and construct a new approximation algorithm for deriving the performance characteristics. It is based on the use of interrupted Poisson processes. The algorithm is shown to be very accurate, and can be used for the optimization of the hold back levels, the parameters of this class of policies. Also, we study related inventory models, where a single stock point servers multiple customers classes. Furthermore, the pooling of server capacity is studied. For a two queue model where the head-of-line processor sharing discipline is applied, we derive the optimal control policy for dividing the servers attention, as well as for accepting customers. Also, a server farm with an infinite number of servers is studied, where servers can be turned off after a service completion in order to save costs. We characterize the optimal policy for this model. In the second part of the thesis polling models are studied, which are queueing systems where multiple queues are served by a single server. An application is the production of multiple types of products on a single machine. In this way, the production capacity is pooled between the product types. For the classical polling model, we derive a closedform approximation for the mean waiting time at each of the queues. The approximation is based on the interpolation of light and heavy traffic results. Also, we study a system with so-called smart customers, where the arrival rate at a queue depends on the position of the server. Finally, we invent two new service disciplines (the gated/exhaustive and the ??-gated discipline) for polling models, designed to yield ’fairness and efficiency’ in the mean waiting times. That is, they result in almost equal mean waiting times at each of the queues, without increasing the weighted sum of the mean waiting times too much

Inventory planning for low demand items in online retailing

Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2007.Includes bibliographical references (p. 81).A large online retailer strategically stocks inventory for SKUs with low demand. The motivations are to provide a wide range of selections and faster customer fulfillment service. We assume the online retailer has the technological capability to manage and control the inventory globally: all warehouses act as one to serve the global demand simultaneously. The online retailer will utilize its entire inventory, regardless of location, to serve demand. We study inventory allocation and order fulfillment policies among warehouses for low-demand SKUs at an online retailer. Thus, given the global demand and an order fulfillment policy, there are tradeoffs involving inventory holding costs, transportation costs, and backordering costs in determining the optimal system inventory level and allocation of inventory to warehouses. For the case of Poisson demand and constant replenishment lead time, we develop methods to approximate the key system performance metrics like transshipment, backorders and average system inventory for one-for-one replenishment policies when warehouses hold exactly one unit of inventory. We run computational experiments to test the accuracy of the approximation. We develop extensions for cases when more than one unit of inventory is held at a warehouse.(cont.) We then use these results to develop guidelines for inventory stocking and order fulfillment policies for online retailers. We also compare warehouse allocation policies for conditions when an order arrives but the preferred warehouse does not have stock although there is stock at more than one other location in the system. We develop intuition about the performance of these policies and run simulations to verify our hypotheses about these policies.by Pallav Chhaochhria.S.M