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Dynamic Ground-Holding Policies for a Network of Airports

Author

Listed:
  • Peter B. M. Vranas

    (Department of Naval Architecture and Marine Engineering, National Technical University of Athens)

  • Dimitris Bertsimas

    (Sloan School of Management and Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Amedeo R. Odoni

    (Department of Aeronautics and Astronautics and of Civil Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

The yearly congestion costs in the U.S. airline industry are estimated to be of the order of $2 billion. In P. B. Vranas, Dimitris J. Bertsimas, and A. R. Odoni, The multi-airport ground-holding problem in air traffic control, Operations Research , Vol. 42, pp. 249–261, 1994, we introduced and studied generic integer programming models for the static multi-airport ground-holding problem (GHP), the problem of assigning optimal ground holding delays in a general network of airports, so that the total (ground plus airborne) delay cost of all flights is minimized. The present paper is the first attempt to address the multi-airport GHP in a dynamic environment. We propose algorithms to update ground-holding decisions as time progresses and more accurate weather (hence capacity) forecasts become available. We propose several pure IP formulations (most of them 0–1), which have the important advantages of being remarkably compact while capturing the essential aspects of the problem and of being sufficiently flexible to accommodate various degrees of modeling detail. For example, one formulation allows the dynamic updating of the mix between departure and arrival capacities by modifying runway use. These formulations enable one to assign and dynamically update ground holds to a sizeable portion of the network of the major congested U.S. or European airports. We also present structural insights on the behavior of the problem by means of computational results, and we find that our methods perform much better than a heuristic which may approximate, to some extent, current ground-holding practices.

Suggested Citation

  • Peter B. M. Vranas & Dimitris Bertsimas & Amedeo R. Odoni, 1994. "Dynamic Ground-Holding Policies for a Network of Airports," Transportation Science, INFORMS, vol. 28(4), pages 275-291, November.
  • Handle: RePEc:inm:ortrsc:v:28:y:1994:i:4:p:275-291
    DOI: 10.1287/trsc.28.4.275
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    Citations

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    Cited by:

    1. Dimitris Bertsimas & Sarah Stock Patterson, 2000. "The Traffic Flow Management Rerouting Problem in Air Traffic Control: A Dynamic Network Flow Approach," Transportation Science, INFORMS, vol. 34(3), pages 239-255, August.
    2. Thomas W. M. Vossen & Michael O. Ball, 2006. "Slot Trading Opportunities in Collaborative Ground Delay Programs," Transportation Science, INFORMS, vol. 40(1), pages 29-43, February.
    3. Wong, Jinn-Tsai & Tsai, Shy-Chang, 2012. "A survival model for flight delay propagation," Journal of Air Transport Management, Elsevier, vol. 23(C), pages 5-11.
    4. Guo, Yechenfeng & Hu, Minghua & Zou, Bo & Hansen, Mark & Zhang, Ying & Xie, Hua, 2022. "Air Traffic Flow Management Integrating Separation Management and Ground Holding: An Efficiency-Equity Bi-objective Perspective," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 394-423.
    5. Mohamed Ali Kammoun & Sadok Turki & Nidhal Rezg, 2020. "Optimization of Flight Rescheduling Problem under Carbon Tax," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    6. Bard, Jonathan F. & Mohan, Dinesh Natarajan, 2008. "Reallocating arrival slots during a ground delay program," Transportation Research Part B: Methodological, Elsevier, vol. 42(2), pages 113-134, February.
    7. Gregory D. Glockner & George L. Nemhauser, 2000. "A Dynamic Network Flow Problem with Uncertain arc Capacities: Formulation and Problem Structure," Operations Research, INFORMS, vol. 48(2), pages 233-242, April.
    8. Dimitris Bertsimas & Sarah Stock Patterson, 1998. "The Air Traffic Flow Management Problem with Enroute Capacities," Operations Research, INFORMS, vol. 46(3), pages 406-422, June.
    9. Dixit, Aasheesh & Jakhar, Suresh Kumar, 2021. "Airport capacity management: A review and bibliometric analysis," Journal of Air Transport Management, Elsevier, vol. 91(C).
    10. Churchill, Andrew M. & Lovell, David J., 2012. "Coordinated aviation network resource allocation under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 19-33.
    11. Brunner, Jens O., 2014. "Rescheduling of flights during ground delay programs with consideration of passenger and crew connections," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 236-252.
    12. Agustı´n, A. & Alonso-Ayuso, A. & Escudero, L.F. & Pizarro, C., 2012. "On air traffic flow management with rerouting. Part II: Stochastic case," European Journal of Operational Research, Elsevier, vol. 219(1), pages 167-177.
    13. Montlaur, A. & Delgado, L., 2020. "Flight and passenger efficiency-fairness trade-off for ATFM delay assignment," Journal of Air Transport Management, Elsevier, vol. 83(C).
    14. Chen, Yunxiang & Zhao, Yifei & Wu, Yexin, 2024. "Recent progress in air traffic flow management: A review," Journal of Air Transport Management, Elsevier, vol. 116(C).
    15. Bolić, Tatjana & Castelli, Lorenzo & Corolli, Luca & Scaini, Giovanni, 2021. "Flexibility in strategic flight planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    16. Robert Hoffman & Michael O. Ball, 2000. "A Comparison of Formulations for the Single-Airport Ground-Holding Problem with Banking Constraints," Operations Research, INFORMS, vol. 48(4), pages 578-590, August.
    17. Kammoun, Mohamed Ali & Rezg, Nidhal, 2018. "An efficient hybrid approach for resolving the aircraft routing and rescheduling problem," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 73-87.
    18. Zhang, Yu, 2008. "Real-time Inter-modal Strategies for Airline Schedule Perturbation Recovery and Airport Congestion Mitigation under Collaborative Decision Making (CDM)," University of California Transportation Center, Working Papers qt2k44c9tx, University of California Transportation Center.
    19. Andreatta, Giovanni & Dell'Olmo, Paolo & Lulli, Guglielmo, 2011. "An aggregate stochastic programming model for air traffic flow management," European Journal of Operational Research, Elsevier, vol. 215(3), pages 697-704, December.
    20. Leal de Matos, Paula & Ormerod, Richard, 2000. "The application of operational research to European air traffic flow management - understanding the context," European Journal of Operational Research, Elsevier, vol. 123(1), pages 125-144, May.

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