Dynamic modeling and control of supply chain systems: A review
Computers and Operations Research
Capacity Rationing in Stochastic Rental Systems with Advance Demand Information
Operations Research
Competition and Cooperation in a Two-Stage Supply Chain with Demand Forecasts
Operations Research
A Multiechelon Inventory Problem with Secondary Market Sales
Management Science
A new algorithm and a new heuristic for serial supply systems
Operations Research Letters
Manufacturing & Service Operations Management
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Customers and downstream supply chain partners often place, or can be induced to place, orders in advance of future requirements. We show how to optimally incorporate advance demand information into periodic-review, multiechelon, inventory systems in series. While the state space for series systems appears to be formidably large, we decompose the problem across locations, as in Clark and Scarf (1960), and reduce the state space at each location by using modified echelon inventory positions (that nets known requirements). We prove the optimality of state-dependent, echelon base-stock policies for finite and infinite horizon problems. We also show that myopic policies are optimal and very easy to compute when costs and demands are stationary. We provide managerial insights into the value of advance demand information through a numerical study.