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Multi-fidelity simulation optimisation for airline disruption management

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Multi-fidelity simulation optimisation for airline disruption management. / Rhodes-Leader, Luke; Worthington, David John; Nelson, Barry Lee et al.

2018 Winter Simulation Conference (WSC). IEEE, 2019. p. 2179-2190.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Rhodes-Leader L, Worthington DJ, Nelson BL, Onggo BSS. Multi-fidelity simulation optimisation for airline disruption management. In 2018 Winter Simulation Conference (WSC). IEEE. 2019. p. 2179-2190 doi: 10.1109/WSC.2018.8632329

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@inproceedings{e9dd609da3d64a8e8abdc2ad90ff905e,
title = "Multi-fidelity simulation optimisation for airline disruption management",
abstract = "The airline industry faces many causes of disruption. To minimise financial and reputational impact, the airline must adapt its schedules. Due to the complexity of the environment, simulation is a natural modelling approach. However, the large solution space, time constraints and system constraints make the search for revised schedules difficult. This paper presents a method for the aircraft recovery problem that uses multi-fidelity modelling including a trust region simulation optimisation algorithm to mitigate the computational costs of using high-fidelity simulations with its benefits for providing good estimates of the true performance.",
author = "Luke Rhodes-Leader and Worthington, {David John} and Nelson, {Barry Lee} and Onggo, {Bhakti Satyabuhdi Stephan}",
year = "2019",
month = feb,
day = "4",
doi = "10.1109/WSC.2018.8632329",
language = "English",
pages = "2179--2190",
booktitle = "2018 Winter Simulation Conference (WSC)",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Multi-fidelity simulation optimisation for airline disruption management

AU - Rhodes-Leader, Luke

AU - Worthington, David John

AU - Nelson, Barry Lee

AU - Onggo, Bhakti Satyabuhdi Stephan

PY - 2019/2/4

Y1 - 2019/2/4

N2 - The airline industry faces many causes of disruption. To minimise financial and reputational impact, the airline must adapt its schedules. Due to the complexity of the environment, simulation is a natural modelling approach. However, the large solution space, time constraints and system constraints make the search for revised schedules difficult. This paper presents a method for the aircraft recovery problem that uses multi-fidelity modelling including a trust region simulation optimisation algorithm to mitigate the computational costs of using high-fidelity simulations with its benefits for providing good estimates of the true performance.

AB - The airline industry faces many causes of disruption. To minimise financial and reputational impact, the airline must adapt its schedules. Due to the complexity of the environment, simulation is a natural modelling approach. However, the large solution space, time constraints and system constraints make the search for revised schedules difficult. This paper presents a method for the aircraft recovery problem that uses multi-fidelity modelling including a trust region simulation optimisation algorithm to mitigate the computational costs of using high-fidelity simulations with its benefits for providing good estimates of the true performance.

U2 - 10.1109/WSC.2018.8632329

DO - 10.1109/WSC.2018.8632329

M3 - Conference contribution/Paper

SP - 2179

EP - 2190

BT - 2018 Winter Simulation Conference (WSC)

PB - IEEE

ER -