IDEAS home Printed from https://ideas.repec.org/a/inm/ormsom/v12y2010i1p56-76.html
   My bibliography  Save this article

Robust Controls for Network Revenue Management

Author

Listed:
  • Georgia Perakis

    () (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Guillaume Roels

    () (Anderson School of Management, University of California, Los Angeles, California 90095)

Abstract

Revenue management models traditionally assume that future demand is unknown but can be described by a stochastic process or a probability distribution. Demand is, however, often difficult to characterize, especially in new or nonstationary markets. In this paper, we develop robust formulations for the capacity allocation problem in revenue management using the maximin and the minimax regret criteria under general polyhedral uncertainty sets. Our approach encompasses the following open-loop controls: partitioned booking limits, nested booking limits, displacement-adjusted virtual nesting, and fixed bid prices. In specific problem instances, we show that a booking policy of the type of displacement-adjusted virtual nesting is robust, both from maximin and minimax regret perspectives. Our numerical analysis reveals that the minimax regret controls perform very well on average, despite their worst-case focus, and outperform the traditional controls when demand is correlated or censored. In particular, on real large-scale problem sets, the minimax regret approach outperforms by up to 2% the traditional heuristics. The maximin controls are more conservative but have the merit of being associated with a minimum revenue guarantee. Our models are scalable to solve practical problems because they combine efficient (exact or heuristic) solution methods with very modest data requirements.

Suggested Citation

  • Georgia Perakis & Guillaume Roels, 2010. "Robust Controls for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 12(1), pages 56-76, November.
  • Handle: RePEc:inm:ormsom:v:12:y:2010:i:1:p:56-76
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/msom.1080.0252
    Download Restriction: no

    References listed on IDEAS

    as
    1. 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.
    2. Garrett van Ryzin & Jeff McGill, 2000. "Revenue Management Without Forecasting or Optimization: An Adaptive Algorithm for Determining Airline Seat Protection Levels," Management Science, INFORMS, vol. 46(6), pages 760-775, June.
    3. c{S}. .Ilker Birbil & J. B. G. Frenk & Joaquim A. S. Gromicho & Shuzhong Zhang, 2009. "The Role of Robust Optimization in Single-Leg Airline Revenue Management," Management Science, INFORMS, vol. 55(1), pages 148-163, January.
    4. 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.
    5. Aharon Ben-Tal & Boaz Golany & Arkadi Nemirovski & Jean-Philippe Vial, 2005. "Retailer-Supplier Flexible Commitments Contracts: A Robust Optimization Approach," Manufacturing & Service Operations Management, INFORMS, vol. 7(3), pages 248-271, February.
    6. 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.
    7. Gregory A. Godfrey & Warren B. Powell, 2001. "An Adaptive, Distribution-Free Algorithm for the Newsvendor Problem with Censored Demands, with Applications to Inventory and Distribution," Management Science, INFORMS, vol. 47(8), pages 1101-1112, August.
    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. Lan, Yingjie & Ball, Michael O. & Karaesmen, Itir Z. & Zhang, Jean X. & Liu, Gloria X., 2015. "Analysis of seat allocation and overbooking decisions with hybrid information," European Journal of Operational Research, Elsevier, vol. 240(2), pages 493-504.
    2. Wang, Charles X. & Webster, Scott & Zhang, Sidong, 2014. "Robust price-setting newsvendor model with interval market size and consumer willingness-to-pay," International Journal of Production Economics, Elsevier, vol. 154(C), pages 100-112.
    3. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    4. Aslani, Shirin & Modarres, Mohammad & Sibdari, Soheil, 2014. "On the fairness of airlines’ ticket pricing as a result of revenue management techniques," Journal of Air Transport Management, Elsevier, vol. 40(C), pages 56-64.
    5. Andersson, Jonas & Jörnsten, Kurt & Nonås, Sigrid Lise & Sandal, Leif & Ubøe, Jan, 2013. "A maximum entropy approach to the newsvendor problem with partial information," European Journal of Operational Research, Elsevier, vol. 228(1), pages 190-200.
    6. Ayvaz-Cavdaroglu, Nur & Kachani, Soulaymane & Maglaras, Costis, 2016. "Revenue management with minimax regret negotiations," Omega, Elsevier, vol. 63(C), pages 12-22.
    7. repec:eee:ejores:v:263:y:2017:i:2:p:337-348 is not listed on IDEAS
    8. Wang, Jiamin & Xiao, Baichun, 2017. "A minmax regret price control model for managing perishable products with uncertain parameters," European Journal of Operational Research, Elsevier, vol. 258(2), pages 652-663.

    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:inm:ormsom:v:12:y:2010:i:1:p:56-76. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc). General contact details of provider: http://edirc.repec.org/data/inforea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.