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Analysis of Deterministic LP-Based Booking Limit and Bid Price Controls for Revenue Management

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  • Stefanus Jasin

    (Stephen M. Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109)

  • Sunil Kumar

    (Booth School of Business, University of Chicago, Chicago, Illinois 60637)

Abstract

We study the performance of two popular and widely used heuristics for revenue management known as the booking limit and bid price controls. In contrast to a recent result in the literature where frequent re-solvings of a certain heuristic are shown to significantly reduce revenue loss, we show that the asymptotic revenue loss of either booking limit or bid price control cannot be reduced regardless of the choice of re-solving times and the frequency of re-solving. Moreover, we also show that further variations within the policy classes, such as nested instead of partition booking limit, or certainty equivalent instead of additive bid price, are simply indistinguishable in terms of their order of revenue loss under frequent re-solvings. This negative result highlights the limitation of re-solving deterministic linear programs when the solution is interpreted as either a booking limit or a bid price. Finally, we briefly discuss how to modify the traditional booking limit control to make it more responsive to frequent re-solvings and test its performance using numerical experiments.

Suggested Citation

  • Stefanus Jasin & Sunil Kumar, 2013. "Analysis of Deterministic LP-Based Booking Limit and Bid Price Controls for Revenue Management," Operations Research, INFORMS, vol. 61(6), pages 1312-1320, December.
  • Handle: RePEc:inm:oropre:v:61:y:2013:i:6:p:1312-1320
    DOI: 10.1287/opre.2013.1216
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    References listed on IDEAS

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    Cited by:

    1. Yanzhe (Murray) Lei & Stefanus Jasin & Amitabh Sinha, 2018. "Joint Dynamic Pricing and Order Fulfillment for E-commerce Retailers," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 269-284, May.
    2. Pavithra Harsha & Shivaram Subramanian & Joline Uichanco, 2019. "Dynamic Pricing of Omnichannel Inventories," Service Science, INFORMS, vol. 21(1), pages 47-65, January.
    3. Stefanus Jasin, 2014. "Reoptimization and Self-Adjusting Price Control for Network Revenue Management," Operations Research, INFORMS, vol. 62(5), pages 1168-1178, October.
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    5. Pornpawee Bumpensanti & He Wang, 2020. "A Re-Solving Heuristic with Uniformly Bounded Loss for Network Revenue Management," Management Science, INFORMS, vol. 66(7), pages 2993-3009, July.
    6. Hyun-Soo Ahn & Stefanus Jasin & Philip Kaminsky & Yang Wang, 2018. "Analysis of Deterministic Control and Its Improvements for an Inventory Problem with Multiproduct Batch Differentiation," Operations Research, INFORMS, vol. 66(1), pages 58-78, 1-2.
    7. Hosseinalifam, M. & Marcotte, P. & Savard, G., 2016. "A new bid price approach to dynamic resource allocation in network revenue management," European Journal of Operational Research, Elsevier, vol. 255(1), pages 142-150.
    8. Yuhang Ma & Paat Rusmevichientong & Mika Sumida & Huseyin Topaloglu, 2020. "An Approximation Algorithm for Network Revenue Management Under Nonstationary Arrivals," Operations Research, INFORMS, vol. 68(3), pages 834-855, May.
    9. Stefanus Jasin, 2015. "Performance of an LP-Based Control for Revenue Management with Unknown Demand Parameters," Operations Research, INFORMS, vol. 63(4), pages 909-915, August.
    10. Stefanus Jasin & Amitabh Sinha, 2015. "An LP-Based Correlated Rounding Scheme for Multi-Item Ecommerce Order Fulfillment," Operations Research, INFORMS, vol. 63(6), pages 1336-1351, December.

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