Inventory Management with Advance Demand Information and Flexible Delivery

Tong Wang () and Beril L. Toktay ()
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Tong Wang: Decision Sciences Area, INSEAD, 77305 Fontainebleau, France
Beril L. Toktay: College of Management, Georgia Institute of Technology, Atlanta, Georgia 30308

Management Science, 2008, vol. 54, issue 4, 716-732

Abstract: This paper considers inventory models with advance demand information and flexible delivery. Customers place their orders in advance, and delivery is flexible in the sense that early shipment is allowed. Specifically, an order placed at time t by a customer with demand lead time T should be fulfilled by period t + T; failure to fulfill it within the time window [t, t + T] is penalized. We consider two situations: (1) Customer demand lead times are homogeneous and demand arriving in period t is a scalar d t to be satisfied within T periods. We show that state-dependent (s, S) policies are optimal, where the state represents advance demands outside the supply lead-time horizon. We find that increasing the demand lead time is more beneficial than decreasing the supply lead time. (2) Customers are heterogeneous in their demand lead times. In this case, demands are vectors and may exhibit crossover, necessitating an allocation decision in addition to the ordering decision. We develop a lower-bound approximation based on an allocation assumption, and propose protection-level heuristics that yield upper bounds on the optimal cost. Numerical analysis quantifies the optimality gaps of the heuristics (2% on average for the best heuristic) and the benefit of delivery flexibility (14% on average using the best heuristic), and provides insights into when the heuristics perform the best and when flexibility is most beneficial.

Keywords: stochastic inventory model; advance demand information; flexible delivery (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (26)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:54:y:2008:i:4:p:716-732

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