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Applications of stochastic modeling in air traffic management: Methods, challenges and opportunities for solving air traffic problems under uncertainty

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Applications of stochastic modeling in air traffic management: Methods, challenges and opportunities for solving air traffic problems under uncertainty. / Shone, Robert; Glazebrook, Kevin; Zografos, K. G.
In: European Journal of Operational Research, Vol. 292, No. 1, 01.07.2021, p. 1-26.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Shone, R, Glazebrook, K & Zografos, KG 2021, 'Applications of stochastic modeling in air traffic management: Methods, challenges and opportunities for solving air traffic problems under uncertainty', European Journal of Operational Research, vol. 292, no. 1, pp. 1-26. https://doi.org/10.1016/j.ejor.2020.10.039

APA

Shone, R., Glazebrook, K., & Zografos, K. G. (2021). Applications of stochastic modeling in air traffic management: Methods, challenges and opportunities for solving air traffic problems under uncertainty. European Journal of Operational Research, 292(1), 1-26. https://doi.org/10.1016/j.ejor.2020.10.039

Vancouver

Shone R, Glazebrook K, Zografos KG. Applications of stochastic modeling in air traffic management: Methods, challenges and opportunities for solving air traffic problems under uncertainty. European Journal of Operational Research. 2021 Jul 1;292(1):1-26. Epub 2020 Nov 1. doi: 10.1016/j.ejor.2020.10.039

Author

Shone, Robert ; Glazebrook, Kevin ; Zografos, K. G. / Applications of stochastic modeling in air traffic management : Methods, challenges and opportunities for solving air traffic problems under uncertainty. In: European Journal of Operational Research. 2021 ; Vol. 292, No. 1. pp. 1-26.

Bibtex

@article{ecce7006b5944a8798351c87a9ed73c7,
title = "Applications of stochastic modeling in air traffic management: Methods, challenges and opportunities for solving air traffic problems under uncertainty",
abstract = "In this paper we provide a wide-ranging review of the literature on stochastic modeling applications within aviation, with a particular focus on problems involving demand and capacity management and the mitigation of air traffic congestion. From an operations research perspective, the main techniques of interest include analytical queueing theory, stochastic optimal control, robust optimization and stochastic integer programming. Applications of these techniques include the prediction of operational delays at airports, pre-tactical control of aircraft departure times, dynamic control and allocation of scarce airport resources and various others. We provide a critical review of recent developments in the literature and identify promising research opportunities for stochastic modelers within air traffic management.",
keywords = "OR in airlines, Stochastic modeling, Stochastic optimization, Airport capacity management, Air traffic flow management, Airport slot allocation",
author = "Robert Shone and Kevin Glazebrook and Zografos, {K. G.}",
year = "2021",
month = jul,
day = "1",
doi = "10.1016/j.ejor.2020.10.039",
language = "English",
volume = "292",
pages = "1--26",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier Science B.V.",
number = "1",

}

RIS

TY - JOUR

T1 - Applications of stochastic modeling in air traffic management

T2 - Methods, challenges and opportunities for solving air traffic problems under uncertainty

AU - Shone, Robert

AU - Glazebrook, Kevin

AU - Zografos, K. G.

PY - 2021/7/1

Y1 - 2021/7/1

N2 - In this paper we provide a wide-ranging review of the literature on stochastic modeling applications within aviation, with a particular focus on problems involving demand and capacity management and the mitigation of air traffic congestion. From an operations research perspective, the main techniques of interest include analytical queueing theory, stochastic optimal control, robust optimization and stochastic integer programming. Applications of these techniques include the prediction of operational delays at airports, pre-tactical control of aircraft departure times, dynamic control and allocation of scarce airport resources and various others. We provide a critical review of recent developments in the literature and identify promising research opportunities for stochastic modelers within air traffic management.

AB - In this paper we provide a wide-ranging review of the literature on stochastic modeling applications within aviation, with a particular focus on problems involving demand and capacity management and the mitigation of air traffic congestion. From an operations research perspective, the main techniques of interest include analytical queueing theory, stochastic optimal control, robust optimization and stochastic integer programming. Applications of these techniques include the prediction of operational delays at airports, pre-tactical control of aircraft departure times, dynamic control and allocation of scarce airport resources and various others. We provide a critical review of recent developments in the literature and identify promising research opportunities for stochastic modelers within air traffic management.

KW - OR in airlines, Stochastic modeling, Stochastic optimization, Airport capacity management, Air traffic flow management, Airport slot allocation

U2 - 10.1016/j.ejor.2020.10.039

DO - 10.1016/j.ejor.2020.10.039

M3 - Journal article

VL - 292

SP - 1

EP - 26

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 1

ER -