Flight network-based approach for integrated airline recovery with cruise speed control

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dc.citation.epage1287en_US
dc.citation.issueNumber4en_US
dc.citation.spage1259en_US
dc.citation.volumeNumber51en_US
dc.contributor.authorArıkan, U.en_US
dc.contributor.authorGürel, S.en_US
dc.contributor.authorAktürk, M. S.en_US
dc.date.accessioned2018-04-12T11:01:02Z
dc.date.available2018-04-12T11:01:02Z
dc.date.issued2017en_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.description.abstractAirline 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.en_US
dc.identifier.doi10.1287/trsc.2016.0716en_US
dc.identifier.eissn1526-5447
dc.identifier.issn0041-1655
dc.identifier.urihttp://hdl.handle.net/11693/37040
dc.language.isoEnglishen_US
dc.publisherInstitute for Operations Research and the Management Sciences (I N F O R M S)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1287/trsc.2016.0716en_US
dc.source.titleTransportation Scienceen_US
dc.subjectAirline operationsen_US
dc.subjectConic quadratic mixed integer programmingen_US
dc.subjectCruise speed controlen_US
dc.subjectDisruption managementen_US
dc.subjectFlight networken_US
dc.subjectIntegrated recoveryen_US
dc.subjectIrregular operationsen_US
dc.subjectPassenger recoveryen_US
dc.subjectAir transportationen_US
dc.subjectAircraften_US
dc.subjectInteger programmingen_US
dc.subjectRecoveryen_US
dc.subjectSpeed controlen_US
dc.titleFlight network-based approach for integrated airline recovery with cruise speed controlen_US
dc.typeArticleen_US

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