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Optimizing gate assignments at airport terminals

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  • Haghani, Ali
  • Chen, Min-Ching

Abstract

The assignment of aircraft arriving on schedule to available gates is a major issue during the daily airline operations. The Gate Assignment Problem (GAP) is an easily-understood but difficult to solve problem. An important issue in GAP is to minimize the distance a passenger is required to walk inside the terminal to reach his or her departure gate. The total passenger walking distance is based on the passenger transfer volume between every pair of aircrafts and the distance between every pair of gates. Therefore, the problem of assigning gates to arriving and departing flights at an airport is a Quadratic Assignment Problem (QAP), which is a difficult problem to solve. Recently, integer programming (IP), simulation, and expert systems have been applied to the GAP. A new integer programming formulation of the gate assignment problem is presented. An efficient heuristic solution procedure for solving the problem is also proposed. The performance of this solution approach is evaluated in a variety of test problems, and is compared to the optimal solutions obtained using CPLEX in certain test problems. The proposed heuristic solution approach proves to be an efficient method for obtaining good solutions for large scale gate assignment problems in a very reasonable computation time.

Suggested Citation

  • Haghani, Ali & Chen, Min-Ching, 1998. "Optimizing gate assignments at airport terminals," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(6), pages 437-454, August.
    • Handle: RePEc:eee:transa:v:32:y:1998:i:6:p:437-454
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    1. Loiola, Eliane Maria & de Abreu, Nair Maria Maia & Boaventura-Netto, Paulo Oswaldo & Hahn, Peter & Querido, Tania, 2007. "A survey for the quadratic assignment problem," European Journal of Operational Research, Elsevier, vol. 176(2), pages 657-690, January.
    2. Dorndorf, Ulrich & Drexl, Andreas & Nikulin, Yury & Pesch, Erwin, 2005. "Flight gate scheduling: State-of-the-art and recent developments," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 584, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    3. Casado, Silvia & Pacheco, Joaquín & Laguna, Manuel, 2006. "Design of a system for solving the Labor Scheduling Problem in an airport/Diseño de un sistema para la resolución del problema de programación de turnos en un aeropuerto," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 24, pages 641(20á)-64, Agosto.
    4. Narciso, Mercedes E. & Piera, Miquel A., 2015. "Robust gate assignment procedures from an airport management perspective," Omega, Elsevier, vol. 50(C), pages 82-95.
    5. 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.
    6. 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.
    7. James, Tabitha & Rego, Cesar & Glover, Fred, 2009. "A cooperative parallel tabu search algorithm for the quadratic assignment problem," European Journal of Operational Research, Elsevier, vol. 195(3), pages 810-826, June.
    8. Daş, Gülesin Sena & Gzara, Fatma & Stützle, Thomas, 2020. "A review on airport gate assignment problems: Single versus multi objective approaches," Omega, Elsevier, vol. 92(C).
    9. Konstantinos G. Zografos & Michael A. Madas & Konstantinos N. Androutsopoulos, 2017. "Increasing airport capacity utilisation through optimum slot scheduling: review of current developments and identification of future needs," Journal of Scheduling, Springer, vol. 20(1), pages 3-24, February.
    10. Xiao, Mei & Chien, Steven & Schonfeld, Paul & Hu, Dawei, 2020. "Optimizing flight equencing and gate assignment considering terminal configuration and walking time," Journal of Air Transport Management, Elsevier, vol. 86(C).
    11. Zhang, Dong & Klabjan, Diego, 2017. "Optimization for gate re-assignment," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 260-284.
    12. 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.
    13. H Ding & A Lim & B Rodrigues & Y Zhu, 2004. "New heuristics for over-constrained flight to gate assignments," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(7), pages 760-768, July.
    14. Karsu, Özlem & Azizoğlu, Meral & Alanlı, Kerem, 2021. "Exact and heuristic solution approaches for the airport gate assignment problem," Omega, Elsevier, vol. 103(C).
    15. Yan, Shangyao & Shieh, Chi-Yuan & Chen, Miawjane, 2002. "A simulation framework for evaluating airport gate assignments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(10), pages 885-898, December.
    16. Dorndorf, Ulrich & Drexl, Andreas & Nikulin, Yury & Pesch, Erwin, 2007. "Flight gate scheduling: State-of-the-art and recent developments," Omega, Elsevier, vol. 35(3), pages 326-334, June.
    17. Yan, Shangyao & Tang, Ching-Hui, 2007. "A heuristic approach for airport gate assignments for stochastic flight delays," European Journal of Operational Research, Elsevier, vol. 180(2), pages 547-567, July.
    18. Skorupski, Jacek & Żarów, Piotr, 2021. "Dynamic management of aircraft stand allocation," Journal of Air Transport Management, Elsevier, vol. 90(C).
    19. 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).

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