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A Network Airline Revenue Management Framework Based on Decomposition by Origins and Destinations

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  • Ş. İlker Birbil

    (Faculty of Engineering and Natural Sciences, Sabancı University, Orhanlı-Tuzla, 34956 Istanbul, Turkey)

  • J. B. G. Frenk

    (Faculty of Engineering and Natural Sciences, Sabancı University, Orhanlı-Tuzla, 34956 Istanbul, Turkey)

  • Joaquim A. S. Gromicho

    (VU University, 1081 HV Amsterdam, The Netherlands; and ORTEC, 2719 EA Zoetermeer, The Netherlands)

  • Shuzhong Zhang

    (Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota 55455)

Abstract

We propose a framework for solving airline revenue management problems on large networks, where the main concern is to allocate the flight leg capacities to customer requests under fixed class fares. This framework is based on a mathematical programming model that decomposes the network into origin-destination pairs so that each pair can be treated as a single flight-leg problem. We first discuss that the proposed framework is quite generic in the sense that not only several well-known models from the literature fit into this framework, but also many single flight-leg models can be easily extended to a network setting through the prescribed construction. Then, we analyze the structure of the overall mathematical programming model and establish its relationship with other models frequently used in practice. The application of the proposed framework is illustrated through two examples based on static and dynamic single-leg models, respectively. These illustrative examples are then benchmarked against several existing methods on a set of real-life network problems.

Suggested Citation

  • Ş. İlker Birbil & J. B. G. Frenk & Joaquim A. S. Gromicho & Shuzhong Zhang, 2014. "A Network Airline Revenue Management Framework Based on Decomposition by Origins and Destinations," Transportation Science, INFORMS, vol. 48(3), pages 313-333, August.
  • Handle: RePEc:inm:ortrsc:v:48:y:2014:i:3:p:313-333
    DOI: 10.1287/trsc.2013.0469
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Daniel Adelman, 2007. "Dynamic Bid Prices in Revenue Management," Operations Research, INFORMS, vol. 55(4), pages 647-661, August.
    4. 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.
    5. 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.
    6. Barry C. Smith & John F. Leimkuhler & Ross M. Darrow, 1992. "Yield Management at American Airlines," Interfaces, INFORMS, vol. 22(1), pages 8-31, February.
    7. 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.
    8. Dimitris Bertsimas & Ioana Popescu, 2003. "Revenue Management in a Dynamic Network Environment," Transportation Science, INFORMS, vol. 37(3), pages 257-277, August.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Dan Zhang, 2011. "An Improved Dynamic Programming Decomposition Approach for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 13(1), pages 35-52, April.
    14. Nurşen Aydın & Ş. İlker Birbil & J. B. G. Frenk & Nilay Noyan, 2013. "Single-Leg Airline Revenue Management with Overbooking," Transportation Science, INFORMS, vol. 47(4), pages 560-583, November.
    15. Chaoxu Tong & Huseyin Topaloglu, 2014. "On the Approximate Linear Programming Approach for Network Revenue Management Problems," INFORMS Journal on Computing, INFORMS, vol. 26(1), pages 121-134, February.
    16. Huseyin Topaloglu, 2009. "Using Lagrangian Relaxation to Compute Capacity-Dependent Bid Prices in Network Revenue Management," Operations Research, INFORMS, vol. 57(3), pages 637-649, June.
    17. William L. Cooper & Tito Homem-de-Mello, 2007. "Some Decomposition Methods for Revenue Management," Transportation Science, INFORMS, vol. 41(3), pages 332-353, August.
    18. 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.
    19. Sumit Kunnumkal & Huseyin Topaloglu, 2011. "A stochastic approximation algorithm to compute bid prices for joint capacity allocation and overbooking over an airline network," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(4), pages 323-343, June.
    20. Georgia Perakis & Guillaume Roels, 2010. "Robust Controls for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 12(1), pages 56-76, November.
    21. Huseyin Topaloglu, 2008. "A Stochastic Approximation Method to Compute Bid Prices in Network Revenue Management Problems," INFORMS Journal on Computing, INFORMS, vol. 20(4), pages 596-610, November.
    22. Michael O. Ball & Maurice Queyranne, 2009. "Toward Robust Revenue Management: Competitive Analysis of Online Booking," Operations Research, INFORMS, vol. 57(4), pages 950-963, August.
    23. Yigao Liang, 1999. "Solution to the Continuous Time Dynamic Yield Management Model," Transportation Science, INFORMS, vol. 33(1), pages 117-123, February.
    24. 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.
    25. 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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