Resource allocation in congested queueing systems with time-varying demand: An application to airport operations

Rob Shone, Kevin Glazebrook and Konstantinos G. Zografos

European Journal of Operational Research, 2019, vol. 276, issue 2, 566-581

Abstract: Motivated by the need to develop time-efficient methods for minimizing operational delays at severely congested airports, we consider a problem involving the distribution of a common resource between two sources of time-varying demand. We formulate this as a dynamic program in which the objective is based on second moments of stochastic queue lengths and show that, for sufficiently high volumes of demand, optimal values can be well-approximated by quadratic functions of the system state. We identify conditions which enable the strong performance of myopic policies and develop approaches to the design of heuristic policies by means of approximate dynamic programming (ADP) methods. Numerical experiments suggest that our ADP-based heuristics, which require very little computational effort, are able to improve substantially upon the performances of more naive decision-making policies, particularly if exogenous system parameters vary considerably as functions of time.

Keywords: Queueing; Optimization; Approximate dynamic programming; Airport operations; Aviation (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:276:y:2019:i:2:p:566-581

DOI: 10.1016/j.ejor.2019.01.024

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