The capacitated multi-echelon inventory system with serial structure. 1. The 'push ahead'-effect

This paper considers a multi-echelon, periodic review inventory model with discrete demand. We assume finite capacities on various production/order sizes and backordering of excess demand. We show that under the average cost criterion the optimal order strategy may be characterized by a so-called 'push ahead'-effect. Further we shall find that a modified base-stock policy approximates the optimal policy quite well

Optimal capacity in a coordinated supply chain

We consider a supply chain in which a retailer faces a stochastic demand, incurs backorder and inventory holding costs and uses a periodic review system to place orders from a manufacturer. The manufacturer must fill the entire order. The manufacturer incurs costs of overtime and undertime if the order deviates from the planned production capacity. We determine the optimal capacity for the manufacturer in case there is no coordination with the retailer as well as in case there is full coordination with the retailer. When there is no coordination the optimal capacity for the manufacturer is found by solving a newsvendor problem. When there is coordination, we present a dynamic programming formulation and establish that the optimal ordering policy for the retailer is characterized by two parameters. The optimal coordinated capacity for the manufacturer can then be obtained by solving a nonlinear programming problem. We present an efficient exact algorithm and a heuristic algorithm for computing the manufacturer's capacity. We discuss the impact of coordination on the supply chain cost as well as on the manufacturer's capacity. We also identify the situations in which coordination is most beneficial. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58030/1/20271_ftp.pd

Optimal control for production inventory system with various cost criterion

In this article, we investigate a dynamic control problem of a production-inventory system. Here, demands arrive at the production unit according to a Poisson process and are processed in an FCFS manner. The processing time of the customers' demand is the exponential distribution. The production manufacturers produce the items on a make-to-order basis to meet customer demands. The production is run until the inventory level becomes sufficiently large. We assume that an item's production time follows exponential distribution and the amount of time for the produced item to reach the retail shop is negligible. Also, we assume that no new customer joins the queue when there is a void inventory. This yields an explicit product-form solution for the steady-state probability vector of the system. The optimal policy that minimizes the discounted/average/pathwise average total cost per production is derived using a Markov decision process approach. We find optimal policy using value/policy iteration algorithms. Numerical examples are discussed to verify the proposed algorithms.Comment: 5 figure

Inventory management with advance capacity information

One of the important aspects of supply chain management is dealing with demand and supply uncertainty. The uncertainty of future supply can be reduced, if a company is able to obtain advance capacity information (ACI) on future supply/production capacity availability from its supplier. We address a periodic-review inventory system under stochastic demand and stochastic limited supply, for which ACI is available. We show that the optimal ordering policy is a state-dependent base stock policy characterized by a base stock level that is a function of ACI. We establish a link to inventory models using advance demand information (ADI) by developing a capacitated inventory system with ADI, and showing that the model is closely related to the proposed ACI model. Our numerical results reveal several managerial insights. In particular, we show that ACI is most beneficial when there exists sufficient flexibility to react to anticipated demand and supply capacity mismatches. Further, most of the benefits can be reached with only limited future visibility. We also show that the system parameters affecting the value of ACI interact in a complex way, and therefore need to be considered in an integrated manner

Copper and the negative price of storage

Commodities are often stored during periods in which storage returns a negative price. Further, during periods of"backwardation,"the expected revenue from holding inventories will be negative. Since the 1930s, the negative price of storage has been attributed to an offsetting"convenience yield."It has been argued that inventories are a necessary adjunct to business and that increasing inventories from some minimal level reduces overall costs. This theory has always been criticized by proponents of cost-of-carry models, who argue that a negative price for storage creates arbitrage opportunities. Proponents of the cost-of-carry model have asserted that storage will occur only with positive returns. They offer a set of price-arbitrage conditions that associate negative returns with stockouts. Still, stockouts are rare in commodity markets, and storage appears to take place during periods of"backwardation"in apparent violation of the price-arbitrage conditions. For copper, inventories have always been available to the market regardless of the price of storage. The author argues that although inventories may provide a cost-reducing convenience yield, inventories also have value because of uncertainty. Just as the price of a call option contains a premium based on price variability, so the shadow price of inventories contains a dispersion premium associated with the unplanned component of inventories. The author derives a generalized price-arbitrage condition in which either a convenience and/or a dispersion premium may justify inventory holding even during an expected price fall. He uses monthly observations of U.S. producer inventories to estimate the parameters of the price-arbitrage condition. The estimates and simulations he presents are ambiguous with regard to the existence of a convenience yield but strongly support the notion of a dispersion premium for copper. And although the average value of such a premium is low, the value of the premium increases rapidly during periods when inventories are scarce.Environmental Economics&Policies,Common Carriers Industry,Markets and Market Access,Access to Markets,Economic Theory&Research

Optimal Learning Algorithms for Stochastic Inventory Systems with Random Capacities

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156225/2/poms13178_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156225/1/poms13178.pd

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

On multi-stage production/inventory systems under stochastic demand

This paper was presented at the 1992 Conference of the International Society of Inventory Research in Budapest, as a tribute to professor Andrew C. Clark for his inspiring work on multi-echelon inventory models both in theory and practice. It reviews and extends the work of the authors on periodic review serial and convergent multi-echelon systems under stochastic stationary demand. In particular, we highlight the structure of echelon cost functions which play a central role in the derivation of the decomposition results and the optimality of base stock policies. The resulting optimal base stock policy is then compared with an MRP system in terms of cost effectiveness, given a predefined target customer service level. Another extension concerns an at first glance rather different problem; it is shown that the problem of setting safety leadtimes in a multi-stage production-to-order system with stochastic lead times leads to similar decomposition structures as those derived for multi-stage inventory systems. Finally, a discussion on possible extensions to capacitated models, models with uncertainty in both demand and production lead time as well as models with an aborescent structure concludes the paper

Dynamic inventory management with cash flow constraints

In this article, we consider a classic dynamic inventory control problem of a self-financing retailer who periodically replenishes its stock from a supplier and sells it to the market. The replenishment decisions of the retailer are constrained by cash flow, which is updated periodically following purchasing and sales in each period. Excess demand in each period is lost when insufficient inventory is in stock. The retailer's objective is to maximize its expected terminal wealth at the end of the planning horizon. We characterize the optimal inventory control policy and present a simple algorithm for computing the optimal policies for each period. Conditions are identified under which the optimal control policies are identical across periods. We also present comparative statics results on the optimal control policy. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2008Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/61323/1/20322_ftp.pd

Energy-Efficient Transmission Scheduling with Strict Underflow Constraints

We consider a single source transmitting data to one or more receivers/users over a shared wireless channel. Due to random fading, the wireless channel conditions vary with time and from user to user. Each user has a buffer to store received packets before they are drained. At each time step, the source determines how much power to use for transmission to each user. The source's objective is to allocate power in a manner that minimizes an expected cost measure, while satisfying strict buffer underflow constraints and a total power constraint in each slot. The expected cost measure is composed of costs associated with power consumption from transmission and packet holding costs. The primary application motivating this problem is wireless media streaming. For this application, the buffer underflow constraints prevent the user buffers from emptying, so as to maintain playout quality. In the case of a single user with linear power-rate curves, we show that a modified base-stock policy is optimal under the finite horizon, infinite horizon discounted, and infinite horizon average expected cost criteria. For a single user with piecewise-linear convex power-rate curves, we show that a finite generalized base-stock policy is optimal under all three expected cost criteria. We also present the sequences of critical numbers that complete the characterization of the optimal control laws in each of these cases when some additional technical conditions are satisfied. We then analyze the structure of the optimal policy for the case of two users. We conclude with a discussion of methods to identify implementable near-optimal policies for the most general case of M users.Comment: 109 pages, 11 pdf figures, template.tex is main file. We have significantly revised the paper from version 1. Additions include the case of a single receiver with piecewise-linear convex power-rate curves, the case of two receivers, and the infinite horizon average expected cost proble