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

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      Author
      Arıkan, U.
      Gürel, S.
      Aktürk, M. S.
      Date
      2017
      Source 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
      Article
      Item 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 operations
      Conic 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
      Permalink
      http://hdl.handle.net/11693/37040
      Published Version (Please cite this version)
      http://dx.doi.org/10.1287/trsc.2016.0716
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