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Increasing airport capacity utilisation through optimum slot scheduling: review of current developments and identification of future needs

Author

Listed:
  • Konstantinos G. Zografos

    (Lancaster University Management School)

  • Michael A. Madas

    (University of Macedonia)

  • Konstantinos N. Androutsopoulos

    (Athens University of Economics and Business)

Abstract

Most of the busiest airports worldwide experience serious congestion and delay problems which call for some immediate capacity and demand management action. Solutions aiming to manage congestion through better slot scheduling have lately received a great deal of consideration due to their potential for delivering quick and substantial capacity utilisation improvements. A slot scheduling approach brings promises to cope better with congestion problems in the short to medium run and in a more sustainable way based on existing resources. This paper aims to provide a critical review of current research in declared capacity modelling and strategic slot scheduling. Furthermore, it goes beyond the critical review of current research developments by identifying future research issues and gaps and developing concrete directions towards modelling and solving advanced single airport and network-based slot scheduling problems. Our research findings suggest that the next generation of slot scheduling models should explore variations of currently used objectives (e.g., alternative expressions of schedule delay) and most importantly enrich them with fairness and equity, resource utilisation and environmental considerations. Future modelling efforts should also aim to further investigate airlines’ utility of alternative slot allocation outcomes, including various acceptability measures and levels of tolerance against schedule displacements. Last but not least, future research should intensively focus on the development and validation of computationally viable and robust slot scheduling models being able to capture the complexity, dynamic nature and weather-induced uncertainty of airport operations, along with hybrid solution approaches being able to deal with the size and complexity of slot allocation at network level.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:jsched:v:20:y:2017:i:1:d:10.1007_s10951-016-0496-7
    DOI: 10.1007/s10951-016-0496-7
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    3. 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.
    4. Lambelho, Miguel & Mitici, Mihaela & Pickup, Simon & Marsden, Alan, 2020. "Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions," Journal of Air Transport Management, Elsevier, vol. 82(C).
    5. Shone, Rob & Glazebrook, Kevin & Zografos, Konstantinos G., 2019. "Resource allocation in congested queueing systems with time-varying demand: An application to airport operations," European Journal of Operational Research, Elsevier, vol. 276(2), pages 566-581.
    6. Katsigiannis, Fotios A. & Zografos, Konstantinos G., 2023. "Incorporating slot valuation in making airport slot scheduling decisions," European Journal of Operational Research, Elsevier, vol. 308(1), pages 436-454.
    7. Keskin, Merve & Zografos, Konstantinos G., 2023. "Optimal network-wide adjustments of initial airport slot allocations with connectivity and fairness objectives," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
    8. 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).
    9. Zografos, Konstantinos G. & Androutsopoulos, Konstantinos N. & Madas, Michael A., 2018. "Minding the gap: Optimizing airport schedule displacement and acceptability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PA), pages 203-221.
    10. Fu, Xiaowen & Lei, Zheng & Liu, Shaoxuan & Wang, Kun & Yan, Jia, 2020. "On-time performance policy in the Chinese aviation market - An innovation or disruption?," Transport Policy, Elsevier, vol. 95(C), pages 14-23.
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    12. Hu, Rong & Feng, Huilin & Witlox, Frank & Zhang, Junfeng & Connor, Kevin O., 2022. "Airport capacity constraints and air traffic demand in China," Journal of Air Transport Management, Elsevier, vol. 103(C).
    13. Nuno Antunes Ribeiro & Alexandre Jacquillat & António Pais Antunes, 2019. "A Large-Scale Neighborhood Search Approach to Airport Slot Allocation," Transportation Science, INFORMS, vol. 53(6), pages 1772-1797, November.
    14. 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.
    15. 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).
    16. Wang, Chun-Han & Zhang, Wenzhu & Dai, Yue & Lee, Yu-Ching, 2022. "Frequency competition among airlines on coordinated airports network," European Journal of Operational Research, Elsevier, vol. 297(2), pages 484-495.
    17. Yang, Huijuan & Buire, Clara & Delahaye, Daniel & Le, Meilong, 2024. "A heuristic-based multi-objective flight schedule generation framework for airline connectivity optimisation in bank structure: An empirical study on Air China in Chengdu," Journal of Air Transport Management, Elsevier, vol. 116(C).
    18. Androutsopoulos, Konstantinos N. & Manousakis, Eleftherios G. & Madas, Michael A., 2020. "Modeling and solving a bi-objective airport slot scheduling problem," European Journal of Operational Research, Elsevier, vol. 284(1), pages 135-151.
    19. Androutsopoulos, Konstantinos N. & Madas, Michael A., 2019. "Being fair or efficient? A fairness-driven modeling extension to the strategic airport slot scheduling problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 37-60.
    20. Ziming Wang & Chaohao Liao & Xu Hang & Lishuai Li & Daniel Delahaye & Mark Hansen, 2022. "Distribution Prediction of Strategic Flight Delays via Machine Learning Methods," Sustainability, MDPI, vol. 14(22), pages 1-14, November.
    21. Miranda, Victor A.P. & Oliveira, Alessandro V.M., 2018. "Airport slots and the internalization of congestion by airlines: An empirical model of integrated flight disruption management in Brazil," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 201-219.
    22. Ribeiro, Nuno Antunes & Jacquillat, Alexandre & Antunes, António Pais & Odoni, Amedeo, 2019. "Improving slot allocation at Level 3 airports," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 32-54.
    23. Till Kösters & Marlena Meier & Gernot Sieg, 2023. "Effects of the use-it-or-lose-it rule on airline strategy and climate," Working Papers 36, Institute of Transport Economics, University of Muenster.

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