Markovian Demand Inventory Models

Business environments change over time. They are cyclic, show seasonality or just evolve over time. This is certainly true for customer demand. As a result, stationary demand distributions are crude approximations of true customer behavior at best. Yet, most classical stochastic inventory models make this very assumption. This volume is the first to provide a comprehensive treatment of inventory models with Markov-modulated demand. The distribution of demand in these models depends on the state of the environment which evolves according to a Markov process. These models have a broad range of applications. Examples are products with cyclical and seasonal demands, products with distinct life-cycles or products whose demand distribution depends on other environmental or economic factors. The same framework is used to express influences of endogenous factors like promotions on demand. The book takes the reader through a logical progression from finite horizon to infinite horizon models with discounted cost and then to long-run average cost models deploying a method called vanishing discount approach. It develops insights into the existence and structure of optimal ordering policies providing valuable guidance on how to efficiently manage inventories in dynamic business environments