A simulation scenario based mixed integer programming approach to airline reserve crew scheduling under uncertainty
A simulation scenario based mixed integer programming approach to airline reserve crew scheduling under uncertainty
The environment in which airlines operate is uncertain for many reasons, for example due to the effects of weather, traffic or crew unavailability (due to delay or sickness). This work focuses on airline reserve crew scheduling under crew absence uncertainty and delay for an airline operating a single hub and spoke network. Reserve crew can be used to cover absent crew or delayed connecting crew. A fixed number of reserve crew are available for scheduling and each requires a daily standby duty start time. This work proposes a mixed integer programming approach to scheduling the airline’s reserve crew. A simulation of the airline’s operations with stochastic journey time and crew absence inputs (without reserve crew) is used to generate input disruption scenarios for the mixed integer programming simulation scenario model (MIPSSM) formulation. Each disruption scenario corresponds to a record of all of the disruptions that may occur on the day of operation which are solvable by using reserve crew. A set of disruption scenarios form the input of the MIPSSM formulation, which has the objective of finding the reserve crew schedule that minimises the overall level of disruption over the set of input scenarios. Additionally, modifications of the MIPSSM are explored, a heuristic solution approach and a reserve use policy derived from the MIPSSM are introduced. A heuristic based on the proposed MIPSSM outperforms a range of alternative approaches. The heuristic solution approach suggests that including the right disruption scenarios is as important as the quantity of disruption scenarios that are added to the MIPSSM. An investigation into what makes a good set of scenarios is also presented.
335-363
Bayliss, Christopher
5fb04968-5cbf-40d8-84b0-02e8c7e94a59
Atkin, Jason A.D.
10124d52-072d-404b-850d-ccd0cc4e2451
De Maere, Geert
e7718d90-b9f3-4027-a07c-42b755ac24dc
Paelinck, Marc
a1a3bb12-1ac9-48a9-b5d5-e67182ca546f
4 May 2017
Bayliss, Christopher
5fb04968-5cbf-40d8-84b0-02e8c7e94a59
Atkin, Jason A.D.
10124d52-072d-404b-850d-ccd0cc4e2451
De Maere, Geert
e7718d90-b9f3-4027-a07c-42b755ac24dc
Paelinck, Marc
a1a3bb12-1ac9-48a9-b5d5-e67182ca546f
Bayliss, Christopher, Atkin, Jason A.D., De Maere, Geert and Paelinck, Marc
(2017)
A simulation scenario based mixed integer programming approach to airline reserve crew scheduling under uncertainty.
Annals of Operations Research, 252 (2), .
(doi:10.1007/s10479-016-2174-8).
Abstract
The environment in which airlines operate is uncertain for many reasons, for example due to the effects of weather, traffic or crew unavailability (due to delay or sickness). This work focuses on airline reserve crew scheduling under crew absence uncertainty and delay for an airline operating a single hub and spoke network. Reserve crew can be used to cover absent crew or delayed connecting crew. A fixed number of reserve crew are available for scheduling and each requires a daily standby duty start time. This work proposes a mixed integer programming approach to scheduling the airline’s reserve crew. A simulation of the airline’s operations with stochastic journey time and crew absence inputs (without reserve crew) is used to generate input disruption scenarios for the mixed integer programming simulation scenario model (MIPSSM) formulation. Each disruption scenario corresponds to a record of all of the disruptions that may occur on the day of operation which are solvable by using reserve crew. A set of disruption scenarios form the input of the MIPSSM formulation, which has the objective of finding the reserve crew schedule that minimises the overall level of disruption over the set of input scenarios. Additionally, modifications of the MIPSSM are explored, a heuristic solution approach and a reserve use policy derived from the MIPSSM are introduced. A heuristic based on the proposed MIPSSM outperforms a range of alternative approaches. The heuristic solution approach suggests that including the right disruption scenarios is as important as the quantity of disruption scenarios that are added to the MIPSSM. An investigation into what makes a good set of scenarios is also presented.
Text
__filestore.soton.ac.uk_users_cb1c15_mydocuments_archive_A University_latex 1_patat_patat_patat proposed version_PATAT select proceedings_AoORMIPSSM_MIPSSMZIP_by 13th Nov_march 2016_MIPSSMnewSection10.pdf
- Accepted Manuscript
Text
art%3A10.1007%2Fs10479-016-2174-8
- Version of Record
More information
Accepted/In Press date: 15 March 2016
e-pub ahead of print date: 13 April 2016
Published date: 4 May 2017
Organisations:
Operational Research
Identifiers
Local EPrints ID: 390383
URI: http://eprints.soton.ac.uk/id/eprint/390383
PURE UUID: d54d71ee-e642-4643-8ee0-cc08dd4a68c8
Catalogue record
Date deposited: 01 Apr 2016 09:12
Last modified: 15 Mar 2024 05:27
Export record
Altmetrics
Contributors
Author:
Jason A.D. Atkin
Author:
Geert De Maere
Author:
Marc Paelinck
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics