Airline disruption recovery using symbiotic simulation and multi-fidelity modelling
Airline disruption recovery using symbiotic simulation and multi-fidelity modelling
The airlines industry is prone to disruption due to various causes. Whilst an airline may not be able to control the causes of disruption, it can reduce the impact of a disruptive event, such as a mechanical failure, with its response by revising the schedule. Potential actions include swapping aircraft, delaying flights and cancellations. This poster will present our research into how symbiotic simulation could potentially be used to improve the response to a disruptive event by evaluating potential revised schedules. Due to the large solution space, exhaustive searches are infeasible. Our research is investigating the use of multi-fidelity models to help guide the search of the optimisation algorithm, leading to good solutions being generated within the time constraints of disruption management. The poster will present the latest results of our research.
4588-4589
Onggo, Bhakti Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
28 June 2017
Onggo, Bhakti Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Onggo, Bhakti Stephan
(2017)
Airline disruption recovery using symbiotic simulation and multi-fidelity modelling.
Chan, Victor
(ed.)
In 2017 Winter Simulation Conference, WSC 2017.
IEEE.
.
(doi:10.1109/WSC.2017.8248218).
Record type:
Conference or Workshop Item
(Paper)
Abstract
The airlines industry is prone to disruption due to various causes. Whilst an airline may not be able to control the causes of disruption, it can reduce the impact of a disruptive event, such as a mechanical failure, with its response by revising the schedule. Potential actions include swapping aircraft, delaying flights and cancellations. This poster will present our research into how symbiotic simulation could potentially be used to improve the response to a disruptive event by evaluating potential revised schedules. Due to the large solution space, exhaustive searches are infeasible. Our research is investigating the use of multi-fidelity models to help guide the search of the optimisation algorithm, leading to good solutions being generated within the time constraints of disruption management. The poster will present the latest results of our research.
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Published date: 28 June 2017
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Publisher Copyright:
© 2017 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
Venue - Dates:
2017 Winter Simulation Conference, WSC 2017, , Las Vegas, United States, 2017-12-03 - 2017-12-06
Identifiers
Local EPrints ID: 447431
URI: http://eprints.soton.ac.uk/id/eprint/447431
ISSN: 0891-7736
PURE UUID: 65c9da79-47e6-43b8-9afe-0221c498bc1a
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Date deposited: 11 Mar 2021 17:34
Last modified: 17 Mar 2024 03:54
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Editor:
Victor Chan
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