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A Simultaneous Optimization Model for Airport Network Slot Allocation under Uncertain Capacity

Author

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  • Donghai Wang

    (School of Economics and Management, Beihang University, Beijing 100191, China
    Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beijing 100191, China)

  • Qiuhong Zhao

    (School of Economics and Management, Beihang University, Beijing 100191, China
    Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beijing 100191, China)

Abstract

Serious congestion and delay problems exist in most of the busiest airports worldwide because of imbalance between scarce airport slot resources and increasing traffic demand. Various factors, especially weather conditions, exacerbate the demand–capacity imbalance. This paper presents a robust model for simultaneous slot allocation on an airport network in multiple calendar days, considering airport capacity uncertainty. The idea of robust optimization is conducive to sustainable and stable decision-making. Robustness is represented through reducing the potential scheduling conflicts in the worst case. Then the model links the strategic decisions and pre-tactical decisions in air traffic management (ATM) through the tradeoff between strategic discrepancy cost and operational congestion cost. Under the support of the Cplex solver, numerical analyses are taken to validate the characteristics and effectiveness of the proposed model. The results show that the proposed model effectively eliminates the existing and potential scheduling conflicts, and makes effective tradeoffs between airline preference and potential airport congestion risk.

Suggested Citation

  • Donghai Wang & Qiuhong Zhao, 2020. "A Simultaneous Optimization Model for Airport Network Slot Allocation under Uncertain Capacity," Sustainability, MDPI, vol. 12(14), pages 1-14, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:14:p:5512-:d:382004
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    References listed on IDEAS

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    1. Lili Wan & Qiuping Peng & Jiuhe Wang & Yong Tian & Can Xu, 2020. "Evaluation of Airport Sustainability by the Synthetic Evaluation Method: A Case Study of Guangzhou Baiyun International Airport, China, from 2008 to 2017," Sustainability, MDPI, vol. 12(8), pages 1-18, April.
    2. Ribeiro, Nuno Antunes & Jacquillat, Alexandre & Antunes, António Pais & Odoni, Amedeo R. & Pita, João P., 2018. "An optimization approach for airport slot allocation under IATA guidelines," Transportation Research Part B: Methodological, Elsevier, vol. 112(C), pages 132-156.
    3. 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.
    4. Ivanov, Nikola & Netjasov, Fedja & Jovanović, Radosav & Starita, Stefano & Strauss, Arne, 2017. "Air Traffic Flow Management slot allocation to minimize propagated delay and improve airport slot adherence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 183-197.
    5. Alexandre Jacquillat & Amedeo R. Odoni, 2015. "An Integrated Scheduling and Operations Approach to Airport Congestion Mitigation," Operations Research, INFORMS, vol. 63(6), pages 1390-1410, December.
    6. Heidt, Andreas & Helmke, Hartmut & Kapolke, Manu & Liers, Frauke & Martin, Alexander, 2016. "Robust runway scheduling under uncertain conditions," Journal of Air Transport Management, Elsevier, vol. 56(PA), pages 28-37.
    7. Kan Chang & Ken Howard & Rick Oiesen & Lara Shisler & Midori Tanino & Michael C. Wambsganss, 2001. "Enhancements to the FAA Ground-Delay Program Under Collaborative Decision Making," Interfaces, INFORMS, vol. 31(1), pages 57-76, February.
    8. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    9. Lonzius, Marc Christopher & Lange, Anne, 2017. "Robust Scheduling: An Empirical Study of Its Impact on Air Traffic Delays," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 84640, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    10. Lonzius, Marc Christopher & Lange, Anne, 2017. "Robust Scheduling: An Empirical Study of Its Impact on Air Traffic Delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 98-114.
    11. Pellegrini, Paola & Bolić, Tatjana & Castelli, Lorenzo & Pesenti, Raffaele, 2017. "SOSTA: An effective model for the Simultaneous Optimisation of airport SloT Allocation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 99(C), pages 34-53.
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    Cited by:

    1. Liu, Wenjing & Zhao, Qiuhong & Delahaye, Daniel, 2022. "Research on slot allocation for airport network in the presence of uncertainty," Journal of Air Transport Management, Elsevier, vol. 104(C).
    2. Silvia Zaoli & Giovanni Scaini & Lorenzo Castelli, 2021. "Community Detection for Air Traffic Networks and Its Application in Strategic Flight Planning," Sustainability, MDPI, vol. 13(16), pages 1-16, August.

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