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

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 time scale 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.

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