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Air Traffic Flow Management

In: Quantitative Problem Solving Methods in the Airline Industry

Author

Listed:
  • Thomas W. M. Vossen

    (University of Colorado)

  • Robert Hoffman

    (Metron Aviation, Inc.)

  • Avijit Mukherjee

    (University of California, Santa Cruz)

Abstract

Air transportation systems are some of the most complex logistical systems imaginable. The world’s airlines transported over 2.2 billion passengers in 2008, and transported approximately 40% of world trade (measured by value). There are nearly 2,000 airlines worldwide, which have a total fleet of nearly 23,000 aircraft and serve some 3,750 airports through a route network of several million miles managed by around 160 air navigation service providers.

Suggested Citation

  • Thomas W. M. Vossen & Robert Hoffman & Avijit Mukherjee, 2012. "Air Traffic Flow Management," International Series in Operations Research & Management Science, in: Cynthia Barnhart & Barry Smith (ed.), Quantitative Problem Solving Methods in the Airline Industry, edition 127, chapter 0, pages 385-453, Springer.
    • Handle: RePEc:spr:isochp:978-1-4614-1608-1_7
    DOI: 10.1007/978-1-4614-1608-1_7
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    Citations

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    Cited by:

    1. Alexandre Jacquillat & Amedeo R. Odoni, 2015. "An Integrated Scheduling and Operations Approach to Airport Congestion Mitigation," Operations Research, INFORMS, vol. 63(6), pages 1390-1410, December.
    2. 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.
    3. Dal Sasso, Veronica & Djeumou Fomeni, Franklin & Lulli, Guglielmo & Zografos, Konstantinos G., 2019. "Planning efficient 4D trajectories in Air Traffic Flow Management," European Journal of Operational Research, Elsevier, vol. 276(2), pages 676-687.
    4. Jane Lee & Lavanya Marla & Alexandre Jacquillat, 2020. "Dynamic Disruption Management in Airline Networks Under Airport Operating Uncertainty," Transportation Science, INFORMS, vol. 54(4), pages 973-997, July.
    5. Xu, Yan & Dalmau, Ramon & Melgosa, Marc & Montlaur, Adeline & Prats, Xavier, 2020. "A framework for collaborative air traffic flow management minimizing costs for airspace users: Enabling trajectory options and flexible pre-tactical delay management," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 229-255.
    6. Sadeque Hamdan & Oualid Jouini & Ali Cheaitou & Zied Jemai & Tobias Andersson Granberg, 2023. "On the binary formulation of air traffic flow management problems," Annals of Operations Research, Springer, vol. 321(1), pages 267-279, February.
    7. Weihao Ouyang & Xiaohong Zhu, 2023. "Meta-Heuristic Solver with Parallel Genetic Algorithm Framework in Airline Crew Scheduling," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    8. Dimitris Bertsimas & Shubham Gupta, 2016. "Fairness and Collaboration in Network Air Traffic Flow Management: An Optimization Approach," Transportation Science, INFORMS, vol. 50(1), pages 57-76, February.
    9. Xiao, Mingming & Cai, Kaiquan & Abbass, Hussein A., 2018. "Hybridized encoding for evolutionary multi-objective optimization of air traffic network flow: A case study on China," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 35-55.
    10. Dimitris Bertsimas & Allison Chang & Velibor V. Mišić & Nishanth Mundru, 2019. "The Airlift Planning Problem," Transportation Science, INFORMS, vol. 53(3), pages 773-773, May.

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