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The recoverable robust stand allocation problem: a GRU airport case study

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  • Bert Dijk

    (Delft University of Technology)

  • Bruno F. Santos

    (Delft University of Technology)

  • Joao P. Pita

    (GRU Airport)

Abstract

This paper presents an innovative approach to the tactical planning of aircraft remote and contact-stands allocation at airports. We use the concept of recoverable robustness to obtain a recoverable robust solution to the stand allocation problem, a solution that can be recovered by limited means for the included scenarios. Four objective functions are discussed and tested to assess the efficiency of a stand allocation plan. Namely, the minimization of passengers’ walking distance, the minimization of tows, the maximization of the number of passengers allocated to contact-stands, and the maximization of the potential airport commercial revenue. The inclusion of an airport commercial revenue metric in the stand allocation optimization model and the comparison of its performance to the pre-mentioned other objectives is another novelty of this work. The research was developed in collaboration with the Guarulhos International Airport of São Paulo for which the recoverable robust approach was tested for 6 days of operations at the airport. We demonstrate that the solutions obtained with the proposed approach outperform the solutions of a traditional robust approach. In addition, a discussion of the trade-off between the different objectives is provided.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:orspec:v:41:y:2019:i:3:d:10.1007_s00291-018-0525-3
    DOI: 10.1007/s00291-018-0525-3
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    References listed on IDEAS

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    2. Evler, Jan & Asadi, Ehsan & Preis, Henning & Fricke, Hartmut, 2021. "Airline ground operations: Optimal schedule recovery with uncertain arrival times," Journal of Air Transport Management, Elsevier, vol. 92(C).
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    4. Silva, João & Kalakou, Sofia & Andrade, Antonio R., 2023. "Maximizing non-aeronautical revenues in airport terminals using gate assignment and passenger behaviour modelling," Journal of Air Transport Management, Elsevier, vol. 112(C).
    5. 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.

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