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A dynamic programming approach for the aircraft landing problem with aircraft classes

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  • Lieder, Alexander
  • Briskorn, Dirk
  • Stolletz, Raik

Abstract

The capacity of a runway system represents a bottleneck at many international airports. The current practice at airports is to land approaching aircraft on a first-come, first-served basis. An active rescheduling of aircraft landing times increases runway capacity or reduces delays. The problem of finding an optimal schedule for aircraft landings is referred to as the “aircraft landing problem”. The objective is to minimize the total delay of aircraft landings or the respective cost. The necessary separation time between two operations must be met. Due to the complexity of this scheduling problem, recent research has been focused on developing heuristic solution approaches. This article presents a new algorithm that is able to create optimal landing schedules on multiple independent runways for aircraft with positive target landing times and limited time windows. Our numerical experiments show that problems with up to 100 aircraft can be optimally solved within seconds.

Suggested Citation

  • Lieder, Alexander & Briskorn, Dirk & Stolletz, Raik, 2015. "A dynamic programming approach for the aircraft landing problem with aircraft classes," European Journal of Operational Research, Elsevier, vol. 243(1), pages 61-69.
    • Handle: RePEc:eee:ejores:v:243:y:2015:i:1:p:61-69
    DOI: 10.1016/j.ejor.2014.11.027
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    References listed on IDEAS

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    1. Julia Bennell & Mohammad Mesgarpour & Chris Potts, 2013. "Airport runway scheduling," Annals of Operations Research, Springer, vol. 204(1), pages 249-270, April.
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    Citations

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    Cited by:

    1. Rakesh Prakash & Jitamitra Desai & Rajesh Piplani, 2022. "An optimal data-splitting algorithm for aircraft sequencing on a single runway," Annals of Operations Research, Springer, vol. 309(2), pages 587-610, February.
    2. Marie-Sklaerder Vié & Nicolas Zufferey & Roel Leus, 2022. "Aircraft landing planning under uncertain conditions," Journal of Scheduling, Springer, vol. 25(2), pages 203-228, April.
    3. Dönmez, Kadir & Çetek, Cem & Kaya, Onur, 2022. "Air traffic management in parallel-point merge systems under wind uncertainties," Journal of Air Transport Management, Elsevier, vol. 104(C).
    4. Guépet, Julien & Briant, Olivier & Gayon, Jean-Philippe & Acuna-Agost, Rodrigo, 2017. "Integration of aircraft ground movements and runway operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 131-149.
    5. Lieder, Alexander & Stolletz, Raik, 2016. "Scheduling aircraft take-offs and landings on interdependent and heterogeneous runways," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 167-188.
    6. Bo Xu & Weimin Ma & Hui Huang & Lei Yue, 2016. "Weighted Constrained Position Shift Model for Aircraft Arrival Sequencing and Scheduling Problem," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(04), pages 1-22, August.
    7. Han Zhong & Wei Guan & Wenyi Zhang & Shixiong Jiang & Lingling Fan, 2018. "A bi-objective integer programming model for partly-restricted flight departure scheduling," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-18, May.
    8. Zhang, Junfeng & Zhao, Pengli & Zhang, Yu & Dai, Ximei & Sui, Dong, 2020. "Criteria selection and multi-objective optimization of aircraft landing problem," Journal of Air Transport Management, Elsevier, vol. 82(C).
    9. Pasquale Avella & Maurizio Boccia & Carlo Mannino & Igor Vasilyev, 2017. "Time-Indexed Formulations for the Runway Scheduling Problem," Transportation Science, INFORMS, vol. 51(4), pages 1196-1209, November.

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