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Exact and heuristic approaches to the airport stand allocation problem

Author

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  • Guépet, J.
  • Acuna-Agost, R.
  • Briant, O.
  • Gayon, J.P.

Abstract

The Stand Allocation Problem (SAP) consists in assigning aircraft activities (arrival, departure and intermediate parking) to aircraft stands (parking positions) with the objective of maximizing the number of passengers/aircraft at contact stands and minimizing the number of towing movements, while respecting a set of operational and commercial requirements. We first prove that the problem of assigning each operation to a compatible stand is NP-complete by a reduction from the circular arc graph coloring problem. As a corollary, this implies that the SAP is NP-hard. We then formulate the SAP as a Mixed Integer Program (MIP) and strengthen the formulation in several ways. Additionally, we introduce two heuristic algorithms based on a spatial and time decomposition leading to smaller MIPs. The methods are tested on realistic scenarios based on actual data from two major European airports. We compare the performance and the quality of the solutions with state-of-the-art algorithms. The results show that our MIP-based methods provide significant improvements to the solutions outlined in previously published approaches. Moreover, their low computation makes them very practical.

Suggested Citation

  • Guépet, J. & Acuna-Agost, R. & Briant, O. & Gayon, J.P., 2015. "Exact and heuristic approaches to the airport stand allocation problem," European Journal of Operational Research, Elsevier, vol. 246(2), pages 597-608.
    • Handle: RePEc:eee:ejores:v:246:y:2015:i:2:p:597-608
    DOI: 10.1016/j.ejor.2015.04.040
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    References listed on IDEAS

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    Cited by:

    1. Xu, Liang & Zhang, Chao & Xiao, Feng & Wang, Fan, 2017. "A robust approach to airport gate assignment with a solution-dependent uncertainty budget," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 458-478.
    2. Bert Dijk & Bruno F. Santos & Joao P. Pita, 2019. "The recoverable robust stand allocation problem: a GRU airport case study," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(3), pages 615-639, September.
    3. Li, Mingjie & Hao, Jin-Kao & Wu, Qinghua, 2022. "Learning-driven feasible and infeasible tabu search for airport gate assignment," European Journal of Operational Research, Elsevier, vol. 302(1), pages 172-186.
    4. Kim, Junyoung & Goo, Byungju & Roh, Youngjoo & Lee, Chungmok & Lee, Kyungsik, 2023. "A branch-and-price approach for airport gate assignment problem with chance constraints," Transportation Research Part B: Methodological, Elsevier, vol. 168(C), pages 1-26.
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    6. Hagspihl, Thomas & Kolisch, Rainer & Ruf, Christian & Schiffels, Sebastian, 2022. "Dynamic gate configurations at airports: A network optimization approach," European Journal of Operational Research, Elsevier, vol. 301(3), pages 1133-1148.
    7. Zhang, Dong & Klabjan, Diego, 2017. "Optimization for gate re-assignment," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 260-284.
    8. Hu, Rong & Wang, Deyun & Feng, Huilin & Zhang, Junfeng & Pan, Xiaoran & Deng, Songwu, 2024. "Joint gate-runway scheduling considering carbon emissions, airport noise and ground-air coordination," Journal of Air Transport Management, Elsevier, vol. 116(C).
    9. Skorupski, Jacek & Żarów, Piotr, 2021. "Dynamic management of aircraft stand allocation," Journal of Air Transport Management, Elsevier, vol. 90(C).
    10. Bagamanova, Margarita & Mota, Miguel Mujica, 2020. "A multi-objective optimization with a delay-aware component for airport stand allocation," Journal of Air Transport Management, Elsevier, vol. 83(C).
    11. Ulrich Dorndorf & Florian Jaehn & Erwin Pesch, 2017. "Flight gate assignment and recovery strategies with stochastic arrival and departure times," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 65-93, January.

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