TY - GEN
T1 - Airline disruption recovery using symbiotic simulation and multi-fidelity modelling
AU - Rhodes-Leader, Luke
AU - Onggo, Bhakti Stephan
AU - Worthington, David J.
AU - Nelson, Barry L.
N1 - Funding Information:
We gratefully acknowledge the financial support of the EPSRC funded EP/L015692/1 STOR-i Centre for Doctoral Training and the NSF Grant CMMI-1068473. We would also like to thank Nigel Jackson, Richard Standing and Mike Chester for the original research idea and contextual information.
Publisher Copyright:
© 2017 OR Society. All rights reserved.
PY - 2017
Y1 - 2017
N2 - 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 paper 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.
AB - 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 paper 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.
KW - Airline disruption management
KW - Multi-fidelity modelling
KW - Symbiotic simulation
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M3 - Conference contribution
AN - SCOPUS:85048284492
T3 - Proceedings of the Operational Research Society Simulation Workshop 2018, SW 2018
SP - 146
EP - 155
BT - Proceedings of the Operational Research Society Simulation Workshop 2018, SW 2018
A2 - Robertson, Duncan
A2 - Fakhimi, Masoud
A2 - Anagnostou, Anastasia
A2 - Meskarian, Rudabeh
PB - Operational Research Society
T2 - 2018 Operational Research Society Simulation Workshop, SW 2018
Y2 - 19 March 2018 through 21 March 2018
ER -