Optimal Policies for a Capacitated Two-Echelon Inventory System
Operations Research
Optimal Control and Equilibrium Behavior of Production-Inventory Systems
Management Science
Competition and Cooperation in a Two-Stage Supply Chain with Demand Forecasts
Operations Research
Myopic Inventory Policies Using Individual Customer Arrival Information
Manufacturing & Service Operations Management
A Multiechelon Inventory Problem with Secondary Market Sales
Management Science
A sample-path approach to the optimality of echelon order-up-to policies in serial inventory systems
Operations Research Letters
Manufacturing & Service Operations Management
Managing Inventory in Global Supply Chains Facing Port-of-Entry Disruption Risks
Transportation Science
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This paper considers a multistage serial inventory system with Markov-modulated demand. Random demand arises at Stage 1, Stage 1 orders from Stage 2, etc., and StageN orders from an outside supplier with unlimited stock. The demand distribution in each period is determined by the current state of an exogenous Markov chain. Excess demand is backlogged. Linear holding costs are incurred at every stage, and linear backorder costs are incurred at Stage 1. The ordering costs are also linear. The objective is to minimize the long-run average costs in the system. The paper shows that the optimal policy is an echelon base-stock policy with state-dependent order-up-to levels. An efficient algorithm is also provided for determining the optimal base-stock levels. The results can be extended to serial systems in which there is a fixed ordering cost at stageN and to assembly systems with linear ordering costs.