IDEAS home Printed from https://ideas.repec.org/a/spr/topjnl/v29y2021i1d10.1007_s11750-020-00579-6.html
   My bibliography  Save this article

An online optimization-based procedure for the assignment of airplane seats

Author

Listed:
  • Jordi Castro

    (Universitat Politècnica de Catalunya)

  • Fernando Sarachaga

    (Vueling Airlines S.A.)

Abstract

Due to the large number of air flights these days, all procedures involved in their operational management should be carefully optimized. This work presents a novel approach to the seat assignment problem, which focuses on deciding where to seat the passengers of different online purchases. This problem is currently solved by most airlines with a set of simple pre-defined rules that do not take into account future sales. Instead, the approach in this work is based on solving an integer multicommodity network flow problem, where different commodities are associated with expected future demands of different types of passengers. One feature of the developed optimization model is that it has to be solved online (that is, in real time), thus it must be both effective and fast, which prevented the use of more sophisticated (but also more time consuming, as it was experimentally observed) models based on stochastic programming. Using a real database of flights by Vueling Airlines S.A., we generated a set of synthetic online purchases simulating a pseudo-real flight. Applying our approach to this synthetic data, we observed that (1) the optimization model could be satisfactorily solved in real-time using the state-of-the-art CPLEX solver; (2) and the seat assignment obtained was of higher quality than that obtained by the simple pre-defined rules used by airlines.

Suggested Citation

  • Jordi Castro & Fernando Sarachaga, 2021. "An online optimization-based procedure for the assignment of airplane seats," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 204-247, April.
    • Handle: RePEc:spr:topjnl:v:29:y:2021:i:1:d:10.1007_s11750-020-00579-6
    DOI: 10.1007/s11750-020-00579-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11750-020-00579-6
    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/s11750-020-00579-6?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. S. L. Brumelle & J. I. McGill, 1993. "Airline Seat Allocation with Multiple Nested Fare Classes," Operations Research, INFORMS, vol. 41(1), pages 127-137, February.
    2. Fred Glover & Randy Glover & Joe Lorenzo & Claude McMillan, 1982. "The Passenger-Mix Problem in the Scheduled Airlines," Interfaces, INFORMS, vol. 12(3), pages 73-80, June.
    3. Tak C. Lee & Marvin Hersh, 1993. "A Model for Dynamic Airline Seat Inventory Control with Multiple Seat Bookings," Transportation Science, INFORMS, vol. 27(3), pages 252-265, August.
    4. Balaji Gopalakrishnan & Ellis. Johnson, 2005. "Airline Crew Scheduling: State-of-the-Art," Annals of Operations Research, Springer, vol. 140(1), pages 305-337, November.
    5. Agustı´n, A. & Alonso-Ayuso, A. & Escudero, L.F. & Pizarro, C., 2012. "On air traffic flow management with rerouting. Part I: Deterministic case," European Journal of Operational Research, Elsevier, vol. 219(1), pages 156-166.
    6. Agustı´n, A. & Alonso-Ayuso, A. & Escudero, L.F. & Pizarro, C., 2012. "On air traffic flow management with rerouting. Part II: Stochastic case," European Journal of Operational Research, Elsevier, vol. 219(1), pages 167-177.
    7. 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.
    8. Giovanni Felici & Claudio Gentile, 2004. "A Polyhedral Approach for the Staff Rostering Problem," Management Science, INFORMS, vol. 50(3), pages 381-393, March.
    9. Roland Oliver Hales & Sergio García, 2019. "Congress seat allocation using mathematical optimization," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 426-455, October.
    10. Dror, Moshe & Trudeau, Pierre & Ladany, Shaul P., 1988. "Network models for seat allocation on flights," Transportation Research Part B: Methodological, Elsevier, vol. 22(4), pages 239-250, August.
    11. Peter P. Belobaba, 1989. "OR Practice—Application of a Probabilistic Decision Model to Airline Seat Inventory Control," Operations Research, INFORMS, vol. 37(2), pages 183-197, April.
    Full references (including those not matched with items on IDEAS)

    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. Chatwin, Richard E., 2000. "Optimal dynamic pricing of perishable products with stochastic demand and a finite set of prices," European Journal of Operational Research, Elsevier, vol. 125(1), pages 149-174, August.
    2. Garrett van Ryzin & Gustavo Vulcano, 2008. "Simulation-Based Optimization of Virtual Nesting Controls for Network Revenue Management," Operations Research, INFORMS, vol. 56(4), pages 865-880, August.
    3. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    4. Kalyan Talluri & Garrett van Ryzin, 2000. "Revenue management under general discrete choice model of consumer behavior," Economics Working Papers 533, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2001.
    5. Youyi Feng & Baichun Xiao, 2001. "A Dynamic Airline Seat Inventory Control Model and Its Optimal Policy," Operations Research, INFORMS, vol. 49(6), pages 938-949, December.
    6. Peter P Belobaba, 2016. "Optimization models in RM systems: Optimality versus revenue gains," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(3), pages 229-235, July.
    7. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    8. Dimitris Bertsimas & Sanne de Boer, 2005. "Simulation-Based Booking Limits for Airline Revenue Management," Operations Research, INFORMS, vol. 53(1), pages 90-106, February.
    9. de Boer, Sanne V. & Freling, Richard & Piersma, Nanda, 2002. "Mathematical programming for network revenue management revisited," European Journal of Operational Research, Elsevier, vol. 137(1), pages 72-92, February.
    10. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    11. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    12. Feng, Youyi & Xiao, Baichun, 2006. "A continuous-time seat control model for single-leg flights with no-shows and optimal overbooking upper bound," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1298-1316, October.
    13. You, Peng-Sheng, 2001. "Airline seat management with rejection-for-possible-upgrade decision," Transportation Research Part B: Methodological, Elsevier, vol. 35(5), pages 507-524, June.
    14. E. Andrew Boyd & Ioana C. Bilegan, 2003. "Revenue Management and E-Commerce," Management Science, INFORMS, vol. 49(10), pages 1363-1386, October.
    15. Yingjie Lan & Huina Gao & Michael O. Ball & Itir Karaesmen, 2008. "Revenue Management with Limited Demand Information," Management Science, INFORMS, vol. 54(9), pages 1594-1609, September.
    16. Richard Van Slyke & Yi Young, 2000. "Finite Horizon Stochastic Knapsacks with Applications to Yield Management," Operations Research, INFORMS, vol. 48(1), pages 155-172, February.
    17. Wang, Xiubin & Regan, Amelia, 2006. "Dynamic yield management when aircraft assignments are subject to swap," Transportation Research Part B: Methodological, Elsevier, vol. 40(7), pages 563-576, August.
    18. Pak, K. & Piersma, N., 2002. "airline revenue management," ERIM Report Series Research in Management ERS-2002-12-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    19. Pak, K. & Piersma, N., 2002. "Airline revenue management: an overview of OR techniques 1982-2001," Econometric Institute Research Papers EI 2002-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Ladany, S. P., 1996. "Optimal market segmentation of hotel rooms--the non-linear case," Omega, Elsevier, vol. 24(1), pages 29-36, February.

    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:topjnl:v:29:y:2021:i:1:d:10.1007_s11750-020-00579-6. 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.