IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v236y2016i2d10.1007_s10479-013-1424-2.html
   My bibliography  Save this article

Integrated aircraft and passenger recovery with cruise time controllability

Author

Listed:
  • Uğur Arıkan

    (Middle East Technical University)

  • Sinan Gürel

    (Middle East Technical University)

  • M. Selim Aktürk

    (Bilkent University)

Abstract

Disruptions in airline operations can result in infeasibilities in aircraft and passenger schedules. Airlines typically recover aircraft schedules and disruptions in passenger itineraries sequentially. However, passengers are severely affected by disruptions and recovery decisions. In this paper, we present a mathematical formulation for the integrated aircraft and passenger recovery problem that considers aircraft and passenger related costs simultaneously. Using the superimposition of aircraft and passenger itinerary networks, passengers are explicitly modeled in order to use realistic passenger related costs. In addition to the common routing recovery actions, we integrate several passenger recovery actions and cruise speed control in our solution approach. Cruise speed control is a very beneficial action for mitigating delays. On the other hand, it adds complexity to the problem due to the nonlinearity in fuel cost function. The problem is formulated as a mixed integer nonlinear programming (MINLP) model. We show that the problem can be reformulated as conic quadratic mixed integer programming (CQMIP) problem which can be solved with commercial optimization software such as IBM ILOG CPLEX. Our computational experiments have shown that we could handle several simultaneous disruptions optimally on a four-hub network of a major U.S. airline within less than a minute on the average. We conclude that proposed approach is able to find optimal tradeoff between operating and passenger-related costs in real time.

Suggested Citation

  • Uğur Arıkan & Sinan Gürel & M. Selim Aktürk, 2016. "Integrated aircraft and passenger recovery with cruise time controllability," Annals of Operations Research, Springer, vol. 236(2), pages 295-317, January.
  • Handle: RePEc:spr:annopr:v:236:y:2016:i:2:d:10.1007_s10479-013-1424-2
    DOI: 10.1007/s10479-013-1424-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-013-1424-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-013-1424-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ahmad I. Z. Jarrah & Gang Yu & Nirup Krishnamurthy & Ananda Rakshit, 1993. "A Decision Support Framework for Airline Flight Cancellations and Delays," Transportation Science, INFORMS, vol. 27(3), pages 266-280, August.
    2. Stojkovic, Goran & Soumis, François & Desrosiers, Jacques & Solomon, Marius M., 2002. "An optimization model for a real-time flight scheduling problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(9), pages 779-788, November.
    3. Ram Gopalan & Kalyan Talluri, 1998. "Mathematical models in airline schedule planning: A survey," Annals of Operations Research, Springer, vol. 76(0), pages 155-185, January.
    4. Cook, Andrew & Tanner, Graham & Williams, Victoria & Meise, Gerhard, 2009. "Dynamic cost indexing – Managing airline delay costs," Journal of Air Transport Management, Elsevier, vol. 15(1), pages 26-35.
    5. Niloofar Jafari & Seyed Hessameddin Zegordi, 2010. "The airline perturbation problem: considering disrupted passengers," Transportation Planning and Technology, Taylor & Francis Journals, vol. 33(2), pages 203-220, January.
    6. Shan Lan & John-Paul Clarke & Cynthia Barnhart, 2006. "Planning for Robust Airline Operations: Optimizing Aircraft Routings and Flight Departure Times to Minimize Passenger Disruptions," Transportation Science, INFORMS, vol. 40(1), pages 15-28, February.
    7. Cynthia Barnhart & Amy Cohn, 2004. "Airline Schedule Planning: Accomplishments and Opportunities," Manufacturing & Service Operations Management, INFORMS, vol. 6(1), pages 3-22, November.
    8. Jay Graham, R. & Garrow, Laurie A. & Leonard, John D., 2010. "Business travelers’ ticketing, refund, and exchange behavior," Journal of Air Transport Management, Elsevier, vol. 16(4), pages 196-201.
    9. Kohl, Niklas & Larsen, Allan & Larsen, Jesper & Ross, Alex & Tiourine, Sergey, 2007. "Airline disruption management—Perspectives, experiences and outlook," Journal of Air Transport Management, Elsevier, vol. 13(3), pages 149-162.
    10. Jon D. Petersen & Gustaf Sölveling & John-Paul Clarke & Ellis L. Johnson & Sergey Shebalov, 2012. "An Optimization Approach to Airline Integrated Recovery," Transportation Science, INFORMS, vol. 46(4), pages 482-500, November.
    11. Jay M. Rosenberger & Ellis L. Johnson & George L. Nemhauser, 2003. "Rerouting Aircraft for Airline Recovery," Transportation Science, INFORMS, vol. 37(4), pages 408-421, November.
    12. AhmadBeygi, Shervin & Cohn, Amy & Guan, Yihan & Belobaba, Peter, 2008. "Analysis of the potential for delay propagation in passenger airline networks," Journal of Air Transport Management, Elsevier, vol. 14(5), pages 221-236.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Judith Mulder & Willem van Jaarsveld & Rommert Dekker, 2019. "Simultaneous Optimization of Speed and Buffer Times with an Application to Liner Shipping," Transportation Science, INFORMS, vol. 53(2), pages 365-382, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Uğur Arıkan & Sinan Gürel & M. Aktürk, 2016. "Integrated aircraft and passenger recovery with cruise time controllability," Annals of Operations Research, Springer, vol. 236(2), pages 295-317, January.
    2. Naz Yeti̇moğlu, Yücel & Selim Aktürk, M., 2021. "Aircraft and passenger recovery during an aircraft’s unexpected unavailability," Journal of Air Transport Management, Elsevier, vol. 91(C).
    3. Jon D. Petersen & Gustaf Sölveling & John-Paul Clarke & Ellis L. Johnson & Sergey Shebalov, 2012. "An Optimization Approach to Airline Integrated Recovery," Transportation Science, INFORMS, vol. 46(4), pages 482-500, November.
    4. Uğur Arıkan & Sinan Gürel & M. Selim Aktürk, 2017. "Flight Network-Based Approach for Integrated Airline Recovery with Cruise Speed Control," Transportation Science, INFORMS, vol. 51(4), pages 1259-1287, November.
    5. Jane Lee & Lavanya Marla & Alexandre Jacquillat, 2020. "Dynamic Disruption Management in Airline Networks Under Airport Operating Uncertainty," Transportation Science, INFORMS, vol. 54(4), pages 973-997, July.
    6. Kenan, Nabil & Jebali, Aida & Diabat, Ali, 2018. "The integrated aircraft routing problem with optional flights and delay considerations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 355-375.
    7. Khaled, Oumaima & Minoux, Michel & Mousseau, Vincent & Michel, Stéphane & Ceugniet, Xavier, 2018. "A multi-criteria repair/recovery framework for the tail assignment problem in airlines," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 137-151.
    8. Sherali, Hanif D. & Bish, Ebru K. & Zhu, Xiaomei, 2006. "Airline fleet assignment concepts, models, and algorithms," European Journal of Operational Research, Elsevier, vol. 172(1), pages 1-30, July.
    9. Evler, Jan & Asadi, Ehsan & Preis, Henning & Fricke, Hartmut, 2021. "Airline ground operations: Optimal schedule recovery with uncertain arrival times," Journal of Air Transport Management, Elsevier, vol. 92(C).
    10. Stephen J. Maher, 2016. "Solving the Integrated Airline Recovery Problem Using Column-and-Row Generation," Transportation Science, INFORMS, vol. 50(1), pages 216-239, February.
    11. Cadarso, Luis & Marín, Ángel & Maróti, Gábor, 2013. "Recovery of disruptions in rapid transit networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 15-33.
    12. Sato, Keisuke & Fukumura, Naoto, 2012. "Real-time freight locomotive rescheduling and uncovered train detection during disruption," European Journal of Operational Research, Elsevier, vol. 221(3), pages 636-648.
    13. Mazhar Arıkan & Vinayak Deshpande & Milind Sohoni, 2013. "Building Reliable Air-Travel Infrastructure Using Empirical Data and Stochastic Models of Airline Networks," Operations Research, INFORMS, vol. 61(1), pages 45-64, February.
    14. Sinclair, Karine & Cordeau, Jean-François & Laporte, Gilbert, 2014. "Improvements to a large neighborhood search heuristic for an integrated aircraft and passenger recovery problem," European Journal of Operational Research, Elsevier, vol. 233(1), pages 234-245.
    15. M. Selim Aktürk & Alper Atamtürk & Sinan Gürel, 2014. "Aircraft Rescheduling with Cruise Speed Control," Operations Research, INFORMS, vol. 62(4), pages 829-845, August.
    16. Mulder, J. & van Jaarsveld, W.L. & Dekker, R., 2016. "Simultaneous optimization of speed and buffer times for robust transportation systems," Econometric Institute Research Papers EI2016-36, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    17. Wenkai Li & Mark Wallace, 2012. "Disruption Management for Commercial Aviation," Working Papers EMS_2012_18, Research Institute, International University of Japan.
    18. Huang, Zhouchun & Luo, Xiaodong & Jin, Xianfei & Karichery, Sureshan, 2022. "An iterative cost-driven copy generation approach for aircraft recovery problem," European Journal of Operational Research, Elsevier, vol. 301(1), pages 334-348.
    19. Nianyi Wang & Huiling Wang & Shan Pei & Boyu Zhang, 2023. "A Data-Driven Heuristic Method for Irregular Flight Recovery," Mathematics, MDPI, vol. 11(11), pages 1-22, June.
    20. Vaaben, Bo & Larsen, Jesper, 2015. "Mitigation of airspace congestion impact on airline networks," Journal of Air Transport Management, Elsevier, vol. 47(C), pages 54-65.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:236:y:2016:i:2:d:10.1007_s10479-013-1424-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.