Flight network-based approach for integrated airline recovery with cruise speed control
Author
Arıkan, U.
Gürel, S.
Aktürk, M. S.
Date
2017Source Title
Transportation Science
Print ISSN
0041-1655
Electronic ISSN
1526-5447
Publisher
Institute for Operations Research and the Management Sciences (I N F O R M S)
Volume
51
Issue
4
Pages
1259 - 1287
Language
English
Type
ArticleItem Usage Stats
141
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410
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Abstract
Airline schedules are generally tight and fragile to disruptions. Disruptions can have severe effects on existing aircraft routings, crew pairings, and passenger itineraries that lead to high delay and recovery costs. A recovery approach should integrate the recovery decisions for all entities (aircraft, crew, passengers) in the system as recovery decisions about an entity directly affect the others' schedules. Because of the size of airline flight networks and the requirement for quick recovery decisions, the integrated airline recovery problem is highly complex. In the past decade, an increasing effort has been made to integrate passenger and crew related recovery decisions with aircraft recovery decisions both in practice and in the literature. In this paper, we develop a new flight network based representation for the integrated airline recovery problem. Our approach is based on the flowof each aircraft, crewmember, and passenger through the flight network of the airline. The proposed network structure allows common recovery decisions such as departure delays, aircraft/crew rerouting, passenger reaccommodation, ticket cancellations, and flight cancellations. Furthermore, we can implement aircraft cruise speed (flight time) decisions on the flight network. For the integrated airline recovery problem defined over this network, we propose a conic quadratic mixed integer programming formulation that can be solved in reasonable CPU times for practical size instances. Moreover, we place a special emphasis on passenger recovery. In addition to aggregation and approximation methods, our model allows explicit modeling of passengers and evaluating a more realistic measure of passenger delay costs. Finally, we propose methods based on the proposed network representation to control the problem size and to deal with large airline networks. © 2017 INFORMS.
Keywords
Airline operationsConic quadratic mixed integer programming
Cruise speed control
Disruption management
Flight network
Integrated recovery
Irregular operations
Passenger recovery
Air transportation
Aircraft
Integer programming
Recovery
Speed control