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A Dynamic Model for Airline Seat Allocation with Passenger Diversion and No-Shows

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  • Wen Zhao

    (Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801)

  • Yu-Sheng Zheng

    (Department of Operations and Information Management, The Wharton School of the University of Pennsylvania, Philadelphia, Pennsylvania 19104–6366)

Abstract

For airlines selling the same seats on a scheduled flight at different fares, the demand for a fare class is affected not only by the current availability of lower fares but also by the possibility of future availability of them. To address this type of passenger behavior, this paper studies a two-class dynamic seat allocation model, which has two distinctive features. The model assumes first that the discount fare cannot be reopened once closed and, second, that a fraction of the customers are flexible, i.e., while willing to pay the full fare, they would buy discount fare tickets if available. These assumptions not only reflect customers' behavior but also are consistent with a class of existing static models that are widely accepted by the industry.For this model, we derive structural properties of the optimal policy. We show that the optimal policy is a threshold policy: The discount fare should be closed as soon as the number of seats remaining reaches a predetermined threshold, which is a function of the time remaining before departure. We show that the threshold does not always decrease over time, and that its time-monotonicity depends on how the proportion of flexible customers changes over time. Our model explains why airlines close discount fares as the departure time approaches. We also show a close relationship between the optimal policy and the policies suggested by the existing static models (the Littlewood rule and its variants). Our numerical study shows that, for parameters plausible to real applications, the latter policies, although not optimal for our dynamic model, perform well, compared to the performance of the optimal policies.

Suggested Citation

  • Wen Zhao & Yu-Sheng Zheng, 2001. "A Dynamic Model for Airline Seat Allocation with Passenger Diversion and No-Shows," Transportation Science, INFORMS, vol. 35(1), pages 80-98, February.
  • Handle: RePEc:inm:ortrsc:v:35:y:2001:i:1:p:80-98
    DOI: 10.1287/trsc.35.1.80.10145
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    References listed on IDEAS

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    Cited by:

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    2. Wai Hung Wong & Anming Zhang & Yer Van Hui & Lawrence C. Leung, 2009. "Optimal Baggage-Limit Policy: Airline Passenger and Cargo Allocation," Transportation Science, INFORMS, vol. 43(3), pages 355-369, August.
    3. 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.
    4. V Sri Vanamalla & R Parthasarathy, 2011. "Incentive mechanism to control customer buy-down behaviour," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(8), pages 1566-1573, August.
    5. Vinayak Deshpande & Morris A. Cohen & Karen Donohue, 2003. "A Threshold Inventory Rationing Policy for Service-Differentiated Demand Classes," Management Science, INFORMS, vol. 49(6), pages 683-703, June.
    6. Dan Zhang & Daniel Adelman, 2009. "An Approximate Dynamic Programming Approach to Network Revenue Management with Customer Choice," Transportation Science, INFORMS, vol. 43(3), pages 381-394, August.
    7. Kannapha Amaruchkul & William L. Cooper & Diwakar Gupta, 2007. "Single-Leg Air-Cargo Revenue Management," Transportation Science, INFORMS, vol. 41(4), pages 457-469, November.
    8. Alec Morton, 2006. "Structural properties of network revenue management models: An economic perspective," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(8), pages 748-760, December.
    9. Marco Alderighi & Alessandro Cento & Peter Nijkamp & Piet Rietveld, 2011. "Second-degree Price Discrimination and Inter-group Effects in Airline Routes between European Cities," Tinbergen Institute Discussion Papers 11-118/3, Tinbergen Institute.
    10. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    11. Robert A. Shumsky & Fuqiang Zhang, 2009. "Dynamic Capacity Management with Substitution," Operations Research, INFORMS, vol. 57(3), pages 671-684, June.
    12. Dan Zhang & William L. Cooper, 2005. "Revenue Management for Parallel Flights with Customer-Choice Behavior," Operations Research, INFORMS, vol. 53(3), pages 415-431, June.
    13. Yihua Li & Lila Rasekh & Xiubin Bruce Wang & Qing Miao, 2016. "Stochastic model for hotel room pricing and upgrading," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(6), pages 500-508, December.
    14. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
    15. Cynthia Barnhart & Peter Belobaba & Amedeo R. Odoni, 2003. "Applications of Operations Research in the Air Transport Industry," Transportation Science, INFORMS, vol. 37(4), pages 368-391, November.
    16. Becher, Michael, 2009. "Simultaneous capacity and price control based on fuzzy controllers," International Journal of Production Economics, Elsevier, vol. 121(2), pages 365-382, October.

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