Inventory and Supply Chain Management with Forecast Updates is concerned with the problems of inventory and supply chain decision making with information updating over time. The models considered include inventory decisions with multiple sources and delivery modes, supply-contract design and evaluation, contracts with exercise price, volume-flexible contracts allowing for spot-market purchase decisions, and competitive supply chains. Real problems are formulated into tractable mathematical models, which allow for an analysis of various approaches, and provide insights for better supply chain management. The book provides a unified treatment of these models, presents a critique of the existing results, and points out potential research directions. Attention is focused on solutions – that is, inventory decisions prior and subsequent to information updates and the impact of the quality of information on these decisions.

This edited volume contains 16 research articles. It presents recent and pressing issues in stochastic processes, control theory, differential games, optimization, and their applications in finance, manufacturing, queueing networks, and climate control. One of the salient features is that the book is highly multi-disciplinary. The book is dedicated to Professor Suresh Sethi on the occasion of his 60th birthday, in view of his distinguished career.

This book develops a modeling framework to analyze the problem of inventory management with alternative delivery times. The general context considered here is that a seller replenishes its inventory in fixed intervals and, between replenishments, allocates the limited inventory to satisfy customers who are both price and delivery-time sensitive. On the demand side, customers have heterogeneous delivery-time requirements and choose either spot or late delivery. This theoretical modeling captures the essence of real-world business practices such as the delivery time market segmentation strategy adopted by automobile dealerships in China and many other similar examples. The book focuses on the seller’s optimal inventory replenishment and demand fulfillment policies, and our results provide managerial insights into the merits of flexible delivery-time options. Similar applications such as the group-buying mechanism are also examined. The main mathematical tool used in theoretical analysis is dynamic programming. This book is written for students, researchers, and practitioners in the areas of operations management and industrial engineering who are interested in understanding the rationale of flexible delivery times and designing successful applications.

Coordinating contracts have been extensively researched in supply chain management. In this retrospect, we systematically review the profit allocation, decision sequence, and compliance aspects of these contracts. In addition to the existing concepts in the literature, we propose the notion of sample-path flexibility in profit allocation. Based on precise mathematical definitions, we develop structural properties and characterize sufficient conditions for flexibility in profit allocation, sequence independence, and voluntary compliance. We also obtain sufficient conditions for coordinating supply chains involving fairness-preferred or downside-risk-averse agents with sample-path flexible and voluntary compliant contracts. We reveal that sample-path flexible contracts must have a transaction after uncertainty is realized and that transactions both before and after uncertainty realization adds to their flexibility. With the properties and conditions in hand, we develop a 3 9 3 matrix framework of the coordination aspects within which several well-studied supply chain contracts can be systematically classified. Furthermore, we provide the steps to design coordinating contracts with sample-path flexibility and voluntary compliance, along.

This case study examines how Toyota China is using demand forecasting, production planning, and customer management techniques to align supply and demand in China's fast-growing automotive market. The authors illuminate the China market's unique channels and challenges, including requirements to project sales for new models with no historical data. They focus on realistic issues and challenges throughout, offering exceptional value to both students and practitioners. Authors: Xiaoying Liang, City University of Hong Kong; Lijun Ma, Shenzhen University; Houmin Yan, City University of Hong Kong.

This paper studies a supply chain consisting of two suppliers and one retailer in a spot market, where the retailer uses the newsvendor solution as its purchase policy, and suppliers compete for the retailer's purchase. Since each supplier's bidding strategy affects the other's profit, a game theory approach is used to identify optimal bidding strategies. We prove the existence and uniqueness of a Nash solution. It is also shown that the competition between the supplier leads to a lower market clearing price, and as a result, the retailer benefits from it. Finally, we demonstrate the applicability of the obtained results by deriving optimal bidding strategies for power generator plants in the deregulated California energy market.

We study a single-period two-stage service-constrained supply chain with an information update. The buyer has two procurement opportunities with the second one after observing a market signal, which updates the demand forecast. He also commits to a service level after observing the market signal. We derive his optimal ordering decisions and show that the critical market signal, the optimal first-stage order quantity, and the optimal expected profit are monotone with respect to the target service level. We also discuss the impact of the forecast quality on the optimal decisions. We show that the optimal first-stage order quantity may not be monotone with respect to information accuracy, as is in the case without the service constraint. In addition, we extend our analysis to the situation when an order cancellation is allowed upon the observation of the market signal. We also compare the results obtained for the problems with and without an order cancellation. Finally, we discuss the supply chain coordination issue and find that a buyback contract can also coordinate the supply chain in the presence of the service constraint.

This paper is concerned with a periodic review inventory system with fast and slow delivery modes, fixed ordering cost, and regular demand forecast updates. At the beginning of each period, on-hand inventory and demand information are updated. At the same time, decisions on how much to order using fast and slow delivery modes are made. Fast and slow orders are delivered at the end of the current period and at the end of the next period, respectively. A forecast-update-dependent (s, S)-type policy is shown to be optimal. Also shown are some monotonicity properties of the policy parameters with respect to the costs and information updates.

This paper compares several different production control policies in terms of their robustness to random disturbances such as machine failures, demand fluctuations, and system parameter changes. Simulation models based on VLSI wafer fabrication facilities are utilized to test the performance of the policies. Three different criteria, namely, the average total WIP, the average backlog, and a cost function combining these measures, are used to evaluate performance. Among the policies tested, the Two-Boundary Control policy outperforms the others.

We present a periodic review inventory model with multiple delivery modes. We generalize the notion of the base-stock policy for inventory systems with multiple delivery modes. While base-stock policies are optimal for one or two consecutive delivery modes, it is not so otherwise. For multiple consecutive delivery modes, we show that only the fastest two modes have optimal base stocks, and provide simple counterexamples to show that the remaining ones do not in general. We investigate why the base-stock policy is not optimal through detailed analyses of two numerical examples.