Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 276, Issue 2, Pages 566-581Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejor.2019.01.024
Keywords
Queueing; Optimization; Approximate dynamic programming; Airport operations; Aviation
Funding
- Engineering and Physical Sciences Research Council (EPSRC) [EP/M020258/1]
- EPSRC [EP/M020258/1] Funding Source: UKRI
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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. (C) 2019 The Authors. Published by Elsevier B.V.
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