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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.
revenue management, dynamic pricing, market uncertainty, queueing, state-dependent queues, asymptotic analysis
Besbes, O., & Maglaras, C. (2009). Revenue Optimization for a Make-to-Order Queue in an Uncertain Market Environment. Operations Research, 57 (6), 1438-1450. http://dx.doi.org/10.1287/opre.1080.0645
Date Posted: 27 November 2017
This document has been peer reviewed.