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Unconstraining Methods in Revenue Management Systems: Research Overview and Prospects

Author

Listed:
  • Peng Guo
  • Baichun Xiao
  • Jun Li

Abstract

Demand unconstraining is one of the key techniques to the success of revenue management systems. This paper surveys the history of research on unconstraining methods and reviews over 130 references including the latest research works in the area. We discuss the relationship between censored data unconstraining and forecasting and review five alternative unconstraining approaches. These methods consider data unconstraining in various situations such as single-class, multi-class, and multi-flight. The paper also proposes some future research questions to bridge the gap between theory and applications.

Suggested Citation

  • Peng Guo & Baichun Xiao & Jun Li, 2012. "Unconstraining Methods in Revenue Management Systems: Research Overview and Prospects," Advances in Operations Research, Hindawi, vol. 2012, pages 1-23, July.
    • Handle: RePEc:hin:jnlaor:270910
    DOI: 10.1155/2012/270910
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    Cited by:

    1. Price, Ilan & Fowkes, Jaroslav & Hopman, Daniel, 2019. "Gaussian processes for unconstraining demand," European Journal of Operational Research, Elsevier, vol. 275(2), pages 621-634.
    2. Fukushi, Mitsuyoshi & Delgado, Felipe & Raveau, Sebastián & Santos, Bruno F., 2022. "CHAIRS: A choice-based air transport simulator applied to airline competition and revenue management," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 297-315.
    3. Luis Cadarso & Vikrant Vaze & Cynthia Barnhart & Ángel Marín, 2017. "Integrated Airline Scheduling: Considering Competition Effects and the Entry of the High Speed Rail," Transportation Science, INFORMS, vol. 51(1), pages 132-154, February.
    4. Banerjee, Nilabhra & Morton, Alec & Akartunalı, Kerem, 2020. "Passenger demand forecasting in scheduled transportation," European Journal of Operational Research, Elsevier, vol. 286(3), pages 797-810.

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