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Dynamic solution to the ground-holding problem in air traffic control

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  • Richetta, Octavio
  • Odoni, Amedeo R.

Abstract

Existing probabilistic solutions to the ground-holding problem in air traffic control are of a static nature, with ground-holds assigned to aircraft at the beginning of daily operations. In this paper we present an optimal dynamic solution that simplifies the structure of the control mechanism by exercising ground-holding on groups of aircraft instead of individual flights. Using stochastic linear programming with recourse, we have been able to solve problem instances for one of the largest airports in the U.S. with just a powerful PC. We illustrate the advantage of the probabilistic dynamic solution over: (a) the static solution; (b) a deterministic solution; and (c) the passive strategy of no ground-holding.

Suggested Citation

  • Richetta, Octavio & Odoni, Amedeo R., 1994. "Dynamic solution to the ground-holding problem in air traffic control," Transportation Research Part A: Policy and Practice, Elsevier, vol. 28(3), pages 167-185, May.
  • Handle: RePEc:eee:transa:v:28:y:1994:i:3:p:167-185
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    Cited by:

    1. Liu, Pei-chen Barry & Hansen, Mark & Mukherjee, Avijit, 2008. "Scenario-based air traffic flow management: From theory to practice," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 685-702, August.
    2. 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.
    3. Caccavale, Maria Virginia & Iovanella, Antonio & Lancia, Carlo & Lulli, Guglielmo & Scoppola, Benedetto, 2014. "A model of inbound air traffic: The application to Heathrow airport," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 116-122.
    4. 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.
    5. 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.
    6. Yang, Lixing & Zhou, Xuesong, 2014. "Constraint reformulation and a Lagrangian relaxation-based solution algorithm for a least expected time path problem," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 22-44.
    7. repec:eee:transb:v:102:y:2017:i:c:p:124-141 is not listed on IDEAS
    8. Stojkovic, Goran & Soumis, Fran├žois & Desrosiers, Jacques & Solomon, Marius M., 2002. "An optimization model for a real-time flight scheduling problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(9), pages 779-788, November.
    9. Ghoneim, Ayman & Abbass, Hussein A., 2016. "A multiobjective distance separation methodology to determine sector-level minimum separation for safe air traffic scenarios," European Journal of Operational Research, Elsevier, vol. 253(1), pages 226-240.
    10. Ryerson, Megan S. & Hansen, Mark & Bonn, James, 2014. "Time to burn: Flight delay, terminal efficiency, and fuel consumption in the National Airspace System," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 286-298.
    11. Mukherjee, Avijit & Hansen, Mark, 2009. "A dynamic rerouting model for air traffic flow management," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 159-171, January.
    12. repec:eee:transe:v:110:y:2018:i:c:p:15-30 is not listed on IDEAS

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