IDEAS home Printed from https://ideas.repec.org/a/pal/jorapm/v15y2016i3d10.1057_rpm.2016.13.html
   My bibliography  Save this article

Optimization models in RM systems: Optimality versus revenue gains

Author

Listed:
  • Peter P Belobaba

    (MIT International Center for Air Transportation)

Abstract

Optimization models in airline revenue management (RM) systems have evolved from single flight leg to network revenue maximization to marginal revenue optimization for less restricted fare structures. This article reviews the most common optimization approaches that have been widely implemented in airline RM systems, with a focus on how the mismatch between model assumptions and reality can affect achievable revenue performance. Simulation findings from the Passenger Origin-Destination Simulator are used to illustrate how robustness and revenue gains, as opposed to theoretical optimality, have driven the widespread adoption of practical optimization models in RM systems.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorapm:v:15:y:2016:i:3:d:10.1057_rpm.2016.13
    DOI: 10.1057/rpm.2016.13
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/rpm.2016.13
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1057/rpm.2016.13?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. 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.
    3. Renwick E. Curry, 1990. "Optimal Airline Seat Allocation with Fare Classes Nested by Origins and Destinations," Transportation Science, INFORMS, vol. 24(3), pages 193-204, August.
    4. Richard D. Wollmer, 1992. "An Airline Seat Management Model for a Single Leg Route When Lower Fare Classes Book First," Operations Research, INFORMS, vol. 40(1), pages 26-37, February.
    5. 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.
    6. 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.
    7. Conrad J. Lautenbacher & Shaler Stidham, 1999. "The Underlying Markov Decision Process in the Single-Leg Airline Yield-Management Problem," Transportation Science, INFORMS, vol. 33(2), pages 136-146, May.
    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. Ernst Ahlberg & Irina Mirkina & Alfred Olsson & Christian Söyland & Lars Carlsson, 2023. "On the selection of relevant historical demand data for revenue management applied to transportation," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(4), pages 266-275, August.
    2. Alderighi, Marco & Gaggero, Alberto A. & Piga, Claudio A., 2022. "Hidden prices with fixed inventory: Evidence from the airline industry," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 42-61.
    3. Thomas Fiig & Larry R. Weatherford & Michael D. Wittman, 2019. "Can demand forecast accuracy be linked to airline revenue?," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(4), pages 291-305, August.
    4. Michael D. Wittman & Thomas Fiig & Peter P. Belobaba, 2018. "A dynamic pricing engine for multiple substitutable flights," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(6), pages 420-435, December.
    5. Michael D. Wittman & Peter P. Belobaba, 2018. "Customized dynamic pricing of airline fare products," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(2), pages 78-90, April.
    6. Syed A. M. Shihab & Peng Wei, 2022. "A deep reinforcement learning approach to seat inventory control for airline revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 183-199, April.

    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. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    2. Dimitris Bertsimas & Sanne de Boer, 2005. "Simulation-Based Booking Limits for Airline Revenue Management," Operations Research, INFORMS, vol. 53(1), pages 90-106, February.
    3. 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.
    4. 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.
    5. E. Andrew Boyd & Ioana C. Bilegan, 2003. "Revenue Management and E-Commerce," Management Science, INFORMS, vol. 49(10), pages 1363-1386, October.
    6. 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.
    7. 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.
    8. 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.
    9. Kavitha Balaiyan & R. K. Amit & Atul Kumar Malik & Xiaodong Luo & Amit Agarwal, 2019. "Joint forecasting for airline pricing and revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(6), pages 465-482, December.
    10. 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.
    11. Wang, Weidi & Tang, Ou & Huo, Jiazhen, 2018. "Dynamic capacity allocation for airlines with multi-channel distribution," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 173-181.
    12. Muzaffer Buyruk & Ertan Güner, 2022. "Personalization in airline revenue management: an overview and future outlook," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 129-139, April.
    13. 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.
    14. Chen, Shaoxiang & Gallego, Guillermo & Li, Michael Z.F. & Lin, Bing, 2010. "Optimal seat allocation for two-flight problems with a flexible demand segment," European Journal of Operational Research, Elsevier, vol. 201(3), pages 897-908, March.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Sumit Kunnumkal & Huseyin Topaloglu, 2009. "A stochastic approximation method for the single-leg revenue management problem with discrete demand distributions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 70(3), pages 477-504, December.
    20. 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.

    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:pal:jorapm:v:15:y:2016:i:3:d:10.1057_rpm.2016.13. 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.palgrave.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.