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Network models for seat allocation on flights

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  • Dror, Moshe
  • Trudeau, Pierre
  • Ladany, Shaul P.

Abstract

This paper examines the problem of proper (optimal) control over the seat allocation on flights. Given a heterogeneous fleet of aircraft types, multi-leg flights, a number of different passenger categories, and cancelations, an airline's objective is to devise an effective system which aids in setting the seat allocation targets for each category of passengers on each flight. This issue is analyzed by a number of authors in the context of economic, simulation based, probabilistic, and mathematical programming studies. We present an attempt to address this problem from the systems prospective emphasizing characteristics such as: passenger cancelations, multi-leg flights, and rolling tactical planning time horizon. Starting from a very simple network flow models for a single flight with a number of intermediate stops, a number of progressively complex models are presented. The airline flights and the seat allocation system are represented as a generalized network flow model (with gains/losses on arcs) with the objective of flow maximization (profit maximization). This modelling approach does not claim to replace the seat allocation approaches presented in Alstrup et al. (1985), Mayer (1976), Richter (1982), Simpson (1985a), and Wang (1983), but rather construct seat allocations utilizing some of those referenced schemes in a parameter setting mode for a large network model. The objective of this paper is not to report on computational experiments, but to present a modeling approach which seems to be promising, if somewhat speculative.

Suggested Citation

  • Dror, Moshe & Trudeau, Pierre & Ladany, Shaul P., 1988. "Network models for seat allocation on flights," Transportation Research Part B: Methodological, Elsevier, vol. 22(4), pages 239-250, August.
  • Handle: RePEc:eee:transb:v:22:y:1988:i:4:p:239-250
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    Cited by:

    1. Chatwin, Richard E., 2000. "Optimal dynamic pricing of perishable products with stochastic demand and a finite set of prices," European Journal of Operational Research, Elsevier, vol. 125(1), pages 149-174, August.
    2. Sherali, Hanif D. & Bish, Ebru K. & Zhu, Xiaomei, 2006. "Airline fleet assignment concepts, models, and algorithms," European Journal of Operational Research, Elsevier, vol. 172(1), pages 1-30, July.
    3. 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.
    4. Hanif D. Sherali & Ebru K. Bish & Xiaomei Zhu, 2005. "Polyhedral Analysis and Algorithms for a Demand-Driven Refleeting Model for Aircraft Assignment," Transportation Science, INFORMS, vol. 39(3), pages 349-366, August.
    5. Kalyan Talluri & Garrett van Ryzin, 2000. "Revenue management under general discrete choice model of consumer behavior," Economics Working Papers 533, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2001.
    6. Wang, Xiubin & Wang, Fenghuan, 2007. "Dynamic network yield management," Transportation Research Part B: Methodological, Elsevier, vol. 41(4), pages 410-425, May.
    7. Jordi Castro & Fernando Sarachaga, 2021. "An online optimization-based procedure for the assignment of airplane seats," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 204-247, April.
    8. Ozgun Caliskan Demirag & Julie L. Swann, 2007. "Capacity allocation to sales agents in a decentralized logistics network," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(7), pages 796-810, October.
    9. Garrett van Ryzin & Gustavo Vulcano, 2008. "Simulation-Based Optimization of Virtual Nesting Controls for Network Revenue Management," Operations Research, INFORMS, vol. 56(4), pages 865-880, August.
    10. Ladany, S. P., 1996. "Optimal market segmentation of hotel rooms--the non-linear case," Omega, Elsevier, vol. 24(1), pages 29-36, February.
    11. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    12. 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.
    13. Xiao, Baichun & Yang, Wei, 2010. "A revenue management model for products with two capacity dimensions," European Journal of Operational Research, Elsevier, vol. 205(2), pages 412-421, September.
    14. Hai Jiang & Cynthia Barnhart, 2009. "Dynamic Airline Scheduling," Transportation Science, INFORMS, vol. 43(3), pages 336-354, August.
    15. Raja Gopalakrishnan & Narayan Rangaraj, 2010. "Capacity Management on Long-Distance Passenger Trains of Indian Railways," Interfaces, INFORMS, vol. 40(4), pages 291-302, August.

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