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OPTIMAL PRODUCTION POLICIES WITH MULTISTAGE STOCHASTIC DEMAND LEAD TIMES

Published online by Cambridge University Press:  30 April 2009

Jung-Hyun Kim ,
Hyun-Soo Ahn  and
Rhonda Righter
Jung-Hyun Kim
Affiliation:
Industrial Engineering and Operations Research, University of California at Berkeley, Berkeley, CA 94720 E-mail: javenue@ieor.berkeley.edu
Hyun-Soo Ahn
Affiliation:
Stephen M. Ross School of Business, University of Michigan, Ann Arbor, MI 48109, E-mail: hsahn@umich.edu
Rhonda Righter
Affiliation:
Industrial Engineering and Operations Research, University of California at Berkeley, Berkeley, CA 94720, E-mail: rrighter@ieor.berkeley.edu
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Abstract

We study the value of multistage advance demand information (MADI) in a production system in which customers place an order in advance of their actual need, and each order goes through multiple stages before it becomes due. Any order that is not immediately filled at its due date will be backordered. The producer must decide whether or not to produce based on real-time information regarding current and future orders. We formulate the problem as a Markov decision process and analyze the impact of the demand information on the production policy and the cost. We show that the optimal production policy is a state-dependent base-stock policy, and we show that it has certain monotonicity properties. We also introduce a simple heuristic policy that is significantly easier to compute and that inherits the structural properties of the optimal policy. In addition, we show that its base-stock levels bound those of the socially optimal policy. Numerical study identifies the conditions under which MADI is most beneficial and shows that the heuristic performs almost as well as the optimal policy when MADI is most beneficial.

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 23 , Issue 3 , July 2009 , pp. 515 - 543
Copyright
Copyright © Cambridge University Press 2009

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