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Inventory management is concerned with matching supply with demand and a central problem in Operations Management. The problem is to find the amount to be produced or purchased in order to maximize the total expected profit or minimize the total expected cost. Over the past two decades, several variations of the formula appeared, mostly in trade journals written by and for inventory managers. A critical assumption in the inventory literature is that the demands in different periods are independent and identically distributed. However, in real life, demands may depend on environmental considerations or the events in the world such as the weather, the state of economy, etc. Moreover, these events are represented by stochastic processes - exogenous or controlled. In Markovian Demand Inventory Models, the authors are concerned with inventory models where these world events are modeled by Markov processes. Their research on Markovian demand inventory models was carried out over a period of ten years beginning in the early nineties.

Most manufacturing systems are large, complex, and operate in an environment of uncertainty. It is common practice to manage such systems in a hierarchical fashion. This book articulates a new theory that shows that hierarchical decision making can in fact lead to a near optimization of system goals. The material in the book cuts across disciplines. It will appeal to graduate students and researchers in applied mathematics, operations management, operations research, and system and control theory.

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.