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Revenue Optimization for a Make-to-Order Queue in an Uncertain Market Environment

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  • Omar Besbes

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Costis Maglaras

    (Graduate School of Business, Columbia University, New York, New York 10027)

Abstract

We consider a revenue-maximizing make-to-order manufacturer that serves a market of price- and delay-sensitive customers and operates in an environment in which the market size varies stochastically over time. A key feature of our analysis is that no model is assumed for the evolution of the market size. We analyze two main settings: (i) the size of the market is observable at any point in time; and (ii) the size of the market is not observable and hence cannot be used for decision making. We focus on high-volume systems that are characterized by large processing capacities and market sizes, and where the latter fluctuate on a slower timescale than that of the underlying production system dynamics. We develop an approach to tackle such problems that is based on an asymptotic analysis and that yields near-optimal policy recommendations for the original system via the solution of a stochastic fluid model.

Suggested Citation

  • Omar Besbes & Costis Maglaras, 2009. "Revenue Optimization for a Make-to-Order Queue in an Uncertain Market Environment," Operations Research, INFORMS, vol. 57(6), pages 1438-1450, December.
    • Handle: RePEc:inm:oropre:v:57:y:2009:i:6:p:1438-1450
    DOI: 10.1287/opre.1080.0645
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    References listed on IDEAS

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    10. Mustafa Akan & Barı ş Ata & Tava Olsen, 2012. "Congestion-Based Lead-Time Quotation for Heterogenous Customers with Convex-Concave Delay Costs: Optimality of a Cost-Balancing Policy Based on Convex Hull Functions," Operations Research, INFORMS, vol. 60(6), pages 1505-1519, December.
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