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

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Resource allocation in congested queueing systems with time-varying demand : An application to airport operations. / Shone, Robert; Glazebrook, Kevin David; Zografos, Konstantinos G.

In: European Journal of Operational Research, Vol. 276, No. 2, 16.07.2019, p. 566-581.

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@article{2d6f8e9c26814cd088bc408f529882fc,
title = "Resource allocation in congested queueing systems with time-varying demand: An application to airport operations",
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",
author = "Robert Shone and Glazebrook, {Kevin David} and Zografos, {Konstantinos G}",
year = "2019",
month = "7",
day = "16",
doi = "10.1016/j.ejor.2019.01.024",
language = "English",
volume = "276",
pages = "566--581",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier Science B.V.",
number = "2",

}

RIS

TY - JOUR

T1 - Resource allocation in congested queueing systems with time-varying demand

T2 - An application to airport operations

AU - Shone, Robert

AU - Glazebrook, Kevin David

AU - Zografos, Konstantinos G

PY - 2019/7/16

Y1 - 2019/7/16

N2 - 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.

AB - 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.

KW - Queueing

KW - Optimization

KW - Approximate dynamic programming

KW - Airport operations

KW - Aviation

U2 - 10.1016/j.ejor.2019.01.024

DO - 10.1016/j.ejor.2019.01.024

M3 - Journal article

VL - 276

SP - 566

EP - 581

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 2

ER -