The recoverable robust tail assignment problem

Froyland, Gary and Maher, Stephen and Wu, Cheng-Lung (2014) The recoverable robust tail assignment problem. Transportation Science, 48 (3). pp. 351-372. ISSN 0041-1655

Full text not available from this repository.

Abstract

Schedule disruptions are commonplace in the airline industry with many flight-delaying events occurring each day. Recently there has been a focus on introducing robustness into airline planning stages to reduce the effect of these disruptions. We propose a recoverable robustness technique as an alternative to robust optimisation to reduce the effect of disruptions and the cost of recovery. We formulate the recoverable robust tail assignment problem (RRTAP) as a stochastic program, solved using column generation in the master and subproblems of the Benders' decomposition. We implement a two-phase algorithm for the Benders' decomposition and identify pareto-optimal cuts. The RRTAP includes costs due to flight delays, cancellation, and passenger rerouting, and the recovery stage includes cancellation, delay, and swapping options. To highlight the benefits of simultaneously solving planning and recovery problems in the RRTAP we compare our tail assignment solution against current approaches from the literature. Using airline data we demonstrate that by developing a better tail assignment plan via the RRTAP framework, one can reduce recovery costs in the event of a disruption

Item Type: Journal Article
Journal or Publication Title: Transportation Science
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/3300/3313
Subjects:
Departments: Lancaster University Management School > Management Science
ID Code: 127111
Deposited By: ep_importer_pure
Deposited On: 29 Aug 2018 08:30
Refereed?: Yes
Published?: Published
Last Modified: 15 Jan 2020 04:38
URI: https://eprints.lancs.ac.uk/id/eprint/127111

Actions (login required)

View Item View Item