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Addressing the Pushback Time Allocation Problem at Heathrow Airport

Author

Listed:
  • Jason A. D. Atkin

    (Automated Scheduling, Optimisation and Planning Research Group, School of Computer Science, The University of Nottingham, Nottingham, NG8 1BB, United Kingdom)

  • Geert De Maere

    (Automated Scheduling, Optimisation and Planning Research Group, School of Computer Science, The University of Nottingham, Nottingham, NG8 1BB, United Kingdom)

  • Edmund K. Burke

    (Department of Computing and Mathematics, University of Stirling, Stirling FK9 4LA, Scotland, United Kingdom)

  • John S. Greenwood

    (NATS CTC, Whiteley, Fareham, Hampshire, PO15 7FL, United Kingdom)

Abstract

This paper considers the problem of allocating pushback times to departing aircraft, specifying the time at which they will be given permission to push back from their allocated stand, start their engines, and commence their taxi to the runway. The aim of this research is to first predict the delay (defined as the waiting time at the stand or runway) for each departure, then to use this to calculate a pushback time such that an appropriate amount of the delay is absorbed at the stand, prior to starting the engines. A two-stage approach is used, where the feasibility of the second stage (pushback time allocation) has to be considered within the first stage (takeoff sequencing). The characteristics of this real-world problem and the differences between it and similar problems are thoroughly discussed, along with a consideration of the important effects of these differences. Differences include a nonlinear objective function with a nonconvex component; the integration of two sequence dependent separation problems; separations that can vary over time; and time-slot extensions. Each of these factors has contributed to the design of the solution algorithm. Results predict significant fuel-burn benefits from absorbing some of the delay as stand hold, as well as delay benefits from indirectly aiding the runway controllers by reducing runway queue sizes. A system for pushback time allocation at London Heathrow has been developed by NATS (formerly National Air Traffic Services) based upon the algorithm described in this paper.

Suggested Citation

  • Jason A. D. Atkin & Geert De Maere & Edmund K. Burke & John S. Greenwood, 2013. "Addressing the Pushback Time Allocation Problem at Heathrow Airport," Transportation Science, INFORMS, vol. 47(4), pages 584-602, November.
    • Handle: RePEc:inm:ortrsc:v:47:y:2013:i:4:p:584-602
    DOI: 10.1287/trsc.1120.0446
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    References listed on IDEAS

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    1. Hamsa Balakrishnan & Bala G. Chandran, 2010. "Algorithms for Scheduling Runway Operations Under Constrained Position Shifting," Operations Research, INFORMS, vol. 58(6), pages 1650-1665, December.
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    4. Jason A. D. Atkin & Edmund K. Burke & John S. Greenwood & Dale Reeson, 2007. "Hybrid Metaheuristics to Aid Runway Scheduling at London Heathrow Airport," Transportation Science, INFORMS, vol. 41(1), pages 90-106, February.
    5. Jason A. D. Atkin & Edmund K. Burke & John S. Greenwood & Dale Reeson, 2009. "An examination of take-off scheduling constraints at London Heathrow airport," Public Transport, Springer, vol. 1(3), pages 169-187, August.
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    Cited by:

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    2. Samà, Marcella & D'Ariano, Andrea & Corman, Francesco & Pacciarelli, Dario, 2018. "Coordination of scheduling decisions in the management of airport airspace and taxiway operations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PB), pages 398-411.
    3. Chen, Shuiwang & Wu, Lingxiao & Ng, Kam K.H. & Liu, Wei & Wang, Kun, 2024. "How airports enhance the environmental sustainability of operations: A critical review from the perspective of Operations Research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    4. Samà, Marcella & D’Ariano, Andrea & D’Ariano, Paolo & Pacciarelli, Dario, 2017. "Scheduling models for optimal aircraft traffic control at busy airports: Tardiness, priorities, equity and violations considerations," Omega, Elsevier, vol. 67(C), pages 81-98.
    5. Daniel Karapetyan & Jason A. D. Atkin & Andrew J. Parkes & Juan Castro-Gutierrez, 2017. "Lessons from building an automated pre-departure sequencer for airports," Annals of Operations Research, Springer, vol. 252(2), pages 435-453, May.

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