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On the asymptotic optimality of the randomized linear program for network revenue management

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  • Topaloglu, Huseyin

Abstract

For network revenue management problems, it is known that the bid prices computed through the so-called deterministic linear program are asymptotically optimal as the capacities on the flight legs and the expected numbers of product requests increase linearly with the same rate. In this paper, we show that the same asymptotic optimality result holds for the bid prices computed through the so-called randomized linear program. We computationally investigate how the performance of the randomized linear program changes with different problem parameters and with the number of samples. The hope is that our asymptotic optimality result and computational experiments will raise awareness for the randomized linear program, which has yet not been popular in the research community or industry.

Suggested Citation

  • Topaloglu, Huseyin, 2009. "On the asymptotic optimality of the randomized linear program for network revenue management," European Journal of Operational Research, Elsevier, vol. 197(3), pages 884-896, September.
    • Handle: RePEc:eee:ejores:v:197:y:2009:i:3:p:884-896
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    References listed on IDEAS

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    1. Kalyan Talluri & Garrett van Ryzin, 1999. "A Randomized Linear Programming Method for Computing Network Bid Prices," Transportation Science, INFORMS, vol. 33(2), pages 207-216, May.
    2. 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.
    3. Daniel Adelman, 2007. "Dynamic Bid Prices in Revenue Management," Operations Research, INFORMS, vol. 55(4), pages 647-661, August.
    4. Dimitris Bertsimas & Ioana Popescu, 2003. "Revenue Management in a Dynamic Network Environment," Transportation Science, INFORMS, vol. 37(3), pages 257-277, August.
    5. 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.
    6. Dimitris Bertsimas & Sanne de Boer, 2005. "Simulation-Based Booking Limits for Airline Revenue Management," Operations Research, INFORMS, vol. 53(1), pages 90-106, February.
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    Cited by:

    1. Huseyin Topaloglu & S. Ilker Birbil & J. B. G. Frenk & Nilay Noyan, 2012. "Tractable Open Loop Policies for Joint Overbooking and Capacity Control Over a Single Flight Leg with Multiple Fare Classes," Transportation Science, INFORMS, vol. 46(4), pages 460-481, November.
    2. Chan Seng Pun & Diego Klabjan & Fikri Karaesmen & Sergey Shebalov, 2016. "Itinerary-based nesting control with upsell," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(2), pages 107-137, April.
    3. Mohammad Vardi & Ali Salmasnia & Ali Ghorbanian & Hadi Mokhtari, 2016. "A bi-objective airline revenue management problem with possible cancellation," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 8(1), pages 20-37.

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