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Strategic Flow Management for Air Traffic Control

Author

Listed:
  • Mostafa Terrab

    (Rensselaer Polytechnic Institute, Troy, New York)

  • Amedeo R. Odoni

    (Massachusetts Institute of Technology, Cambridge, Massachusetts)

Abstract

One of the most important functions of air traffic management systems is the assignment of ground-holding times to flights, i.e., the determination of whether and by how much the take-off of a particular aircraft headed for a congested part of the ATC system should be postponed to reduce the likelihood and extent of airborne delays. In this paper, we will present an analysis of the fundamental case in which flights from many origins must be scheduled for arrival at a single, congested airport. We will describe a set of approaches for addressing a deterministic and a stochastic version of the problem. A minimum cost flow algorithm can be used for the deterministic problem. Under a particular natural assumption regarding the functional form of delay costs, a very efficient, simple algorithm is also available. For the stochastic version, an exact dynamic programming formulation turns out to be impractical for typical instances of the problem and we present a number of heuristic approaches to it. The models and numerical results suggest the potential usefulness of formal decision support tools in developing effective ground-holding strategies. Many methodological and implementation issues, however, still require resolution.

Suggested Citation

  • Mostafa Terrab & Amedeo R. Odoni, 1993. "Strategic Flow Management for Air Traffic Control," Operations Research, INFORMS, vol. 41(1), pages 138-152, February.
    • Handle: RePEc:inm:oropre:v:41:y:1993:i:1:p:138-152
    DOI: 10.1287/opre.41.1.138
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    Citations

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    Cited by:

    1. Michael O. Ball & Robert Hoffman & Avijit Mukherjee, 2010. "Ground Delay Program Planning Under Uncertainty Based on the Ration-by-Distance Principle," Transportation Science, INFORMS, vol. 44(1), pages 1-14, February.
    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. Pellegrini, Paola & Rodriguez, Joaquin, 2013. "Single European Sky and Single European Railway Area: A system level analysis of air and rail transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 57(C), pages 64-86.
    4. 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.
    5. Mukherjee, Avijit, 2004. "Dynamic Stochastic Optimization Models for Air Traffic Flow Management," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2vk8w6nc, Institute of Transportation Studies, UC Berkeley.
    6. 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.
    7. 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.
    8. Zhe Liang & Wanpracha Art Chaovalitwongse & Elsayed A. Elsayed, 2014. "Sequence Assignment Model for the Flight Conflict Resolution Problem," Transportation Science, INFORMS, vol. 48(3), pages 334-350, August.
    9. 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).
    10. Liu, Wenjing & Zhao, Qiuhong & Delahaye, Daniel, 2022. "Research on slot allocation for airport network in the presence of uncertainty," Journal of Air Transport Management, Elsevier, vol. 104(C).
    11. 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.
    12. 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.
    13. 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.
    14. Cynthia Barnhart & Dimitris Bertsimas & Constantine Caramanis & Douglas Fearing, 2012. "Equitable and Efficient Coordination in Traffic Flow Management," Transportation Science, INFORMS, vol. 46(2), pages 262-280, May.
    15. 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.
    16. Wei, P. & Cao, Y. & Sun, D., 2013. "Total unimodularity and decomposition method for large-scale air traffic cell transmission model," Transportation Research Part B: Methodological, Elsevier, vol. 53(C), pages 1-16.
    17. 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.
    18. Sun, D. & Clinet, A. & Bayen, A.M., 2011. "A dual decomposition method for sector capacity constrained traffic flow optimization," Transportation Research Part B: Methodological, Elsevier, vol. 45(6), pages 880-902, July.
    19. Diao, Xudong & Chen, Chun-Hsien, 2018. "A sequence model for air traffic flow management rerouting problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 15-30.

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