IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v307y2023i3p1103-1116.html
   My bibliography  Save this article

Two-stage optimization of airport ferry service delay considering flight uncertainty

Author

Listed:
  • Han, Xue
  • Zhao, Peixin
  • Kong, Dexin

Abstract

As an important part of the ground service for flights parked at remote stands, the scheduling optimization of ferry vehicles is the key factor to improve the apron support capacity. Considering the uncertainty of actual arrival time and departure time of flights, a two-stage optimization model for flight on-time service rate and service delay time is proposed in this paper. At the first stage, a capacity network with four types of nodes and five types of arcs is constructed. By setting appropriate arc capacity and cost parameters, a programming model based on the minimum cost flow is constructed to optimize the number of flights that can be served on time by a limited number of ferry vehicles. At the second stage, a new capacity network and a time-space network combined with a heuristic algorithm are constructed, and integer linear programming models are proposed to optimize the delay time of unserved flights in the first stage. The efficiency of the proposed method is verified by flight data from Beijing Capital International Airport and further analysis is carried out. This study can provide a decision-making reference for the scheduling optimization of airport ferry vehicles.

Suggested Citation

  • Han, Xue & Zhao, Peixin & Kong, Dexin, 2023. "Two-stage optimization of airport ferry service delay considering flight uncertainty," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1103-1116.
  • Handle: RePEc:eee:ejores:v:307:y:2023:i:3:p:1103-1116
    DOI: 10.1016/j.ejor.2022.09.023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221722007512
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2022.09.023?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Schyns, M., 2015. "An ant colony system for responsive dynamic vehicle routing," European Journal of Operational Research, Elsevier, vol. 245(3), pages 704-718.
    2. Zhao, Meng & Li, Xiaopeng & Yin, Jiateng & Cui, Jianxun & Yang, Lixing & An, Shi, 2018. "An integrated framework for electric vehicle rebalancing and staff relocation in one-way carsharing systems: Model formulation and Lagrangian relaxation-based solution approach," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 542-572.
    3. Weiszer, Michal & Chen, Jun & Locatelli, Giorgio, 2015. "An integrated optimisation approach to airport ground operations to foster sustainability in the aviation sector," Applied Energy, Elsevier, vol. 157(C), pages 567-582.
    4. Du, Jia Yan & Brunner, Jens O. & Kolisch, Rainer, 2014. "Planning towing processes at airports more efficiently," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 293-304.
    5. Norin, Anna & Granberg, Tobias Andersson & Yuan, Di & Värbrand, Peter, 2012. "Airport logistics – A case study of the turn-around process," Journal of Air Transport Management, Elsevier, vol. 20(C), pages 31-34.
    6. Kulkarni, Sarang & Krishnamoorthy, Mohan & Ranade, Abhiram & Ernst, Andreas T. & Patil, Rahul, 2018. "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 457-487.
    7. Silvia Padrón & Daniel Guimarans, 2019. "An Improved Method for Scheduling Aircraft Ground Handling Operations From a Global Perspective," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(04), pages 1-25, August.
    8. A Norin & D Yuan & T A Granberg & P V&aauml;rbrand, 2012. "Scheduling de-icing vehicles within airport logistics: a heuristic algorithm and performance evaluation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(8), pages 1116-1125, August.
    9. Enzi, Miriam & Parragh, Sophie N. & Pisinger, David & Prandtstetter, Matthias, 2021. "Modeling and solving the multimodal car- and ride-sharing problem," European Journal of Operational Research, Elsevier, vol. 293(1), pages 290-303.
    10. Zhao, Peixin & Han, Xue & Wan, Di, 2021. "Evaluation of the airport ferry vehicle scheduling based on network maximum flow model," Omega, Elsevier, vol. 99(C).
    11. Guedes, Pablo C. & Borenstein, Denis, 2018. "Real-time multi-depot vehicle type rescheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 217-234.
    12. Xue Han & Peixin Zhao & Qingchun Meng & Shengnan Yin & Di Wan, 2020. "Optimal scheduling of airport ferry vehicles based on capacity network," Annals of Operations Research, Springer, vol. 295(1), pages 163-182, December.
    13. Mahmoudi, Monirehalsadat & Zhou, Xuesong, 2016. "Finding optimal solutions for vehicle routing problem with pickup and delivery services with time windows: A dynamic programming approach based on state–space–time network representations," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 19-42.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xue Han & Peixin Zhao & Qingchun Meng & Shengnan Yin & Di Wan, 2020. "Optimal scheduling of airport ferry vehicles based on capacity network," Annals of Operations Research, Springer, vol. 295(1), pages 163-182, December.
    2. Silvia Padrón & Daniel Guimarans, 2019. "An Improved Method for Scheduling Aircraft Ground Handling Operations From a Global Perspective," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(04), pages 1-25, August.
    3. Zhao, Peixin & Han, Xue & Wan, Di, 2021. "Evaluation of the airport ferry vehicle scheduling based on network maximum flow model," Omega, Elsevier, vol. 99(C).
    4. Lee, Enoch & Cen, Xuekai & Lo, Hong K., 2022. "Scheduling zonal-based flexible bus service under dynamic stochastic demand and Time-dependent travel time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    5. Alonso Tabares, Diego & Mora-Camino, Felix & Drouin, Antoine, 2021. "A multi-time scale management structure for airport ground handling automation," Journal of Air Transport Management, Elsevier, vol. 90(C).
    6. Kuo, Yong-Hong & Leung, Janny M.Y. & Yan, Yimo, 2023. "Public transport for smart cities: Recent innovations and future challenges," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1001-1026.
    7. Yagmur S. Gök & Silvia Padrón & Maurizio Tomasella & Daniel Guimarans & Cemalettin Ozturk, 2023. "Constraint-based robust planning and scheduling of airport apron operations through simheuristics," Annals of Operations Research, Springer, vol. 320(2), pages 795-830, January.
    8. Bao, Dan-Wen & Zhou, Jia-Yi & Zhang, Zi-Qian & Chen, Zhuo & Kang, Di, 2023. "Mixed fleet scheduling method for airport ground service vehicles under the trend of electrification," Journal of Air Transport Management, Elsevier, vol. 108(C).
    9. Schultz, Michael & Evler, Jan & Asadi, Ehsan & Preis, Henning & Fricke, Hartmut & Wu, Cheng-Lung, 2020. "Future aircraft turnaround operations considering post-pandemic requirements," Journal of Air Transport Management, Elsevier, vol. 89(C).
    10. Gong, Manlin & Hu, Yucong & Chen, Zhiwei & Li, Xiaopeng, 2021. "Transfer-based customized modular bus system design with passenger-route assignment optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    11. Boyacı, Burak & Zografos, Konstantinos G., 2019. "Investigating the effect of temporal and spatial flexibility on the performance of one-way electric carsharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 244-272.
    12. Wu, Weitiao & Lin, Yue & Liu, Ronghui & Jin, Wenzhou, 2022. "The multi-depot electric vehicle scheduling problem with power grid characteristics," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 322-347.
    13. Wu, Xin (Bruce) & Lu, Jiawei & Wu, Shengnan & Zhou, Xuesong (Simon), 2021. "Synchronizing time-dependent transportation services: Reformulation and solution algorithm using quadratic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 140-179.
    14. Huang, Kai & An, Kun & Rich, Jeppe & Ma, Wanjing, 2020. "Vehicle relocation in one-way station-based electric carsharing systems: A comparative study of operator-based and user-based methods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    15. Zhang, Wenqing & Liu, Liangliang, 2022. "Exploring non-users' intention to adopt ride-sharing services: Taking into account increased risks due to the COVID-19 pandemic among other factors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 180-195.
    16. Yang, Lixing & Zhou, Xuesong, 2017. "Optimizing on-time arrival probability and percentile travel time for elementary path finding in time-dependent transportation networks: Linear mixed integer programming reformulations," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 68-91.
    17. Kulkarni, Sarang & Krishnamoorthy, Mohan & Ranade, Abhiram & Ernst, Andreas T. & Patil, Rahul, 2018. "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 457-487.
    18. Chen, Jingxu & Wang, Shuaian & Liu, Zhiyuan & Guo, Yanyong, 2018. "Network-based optimization modeling of manhole setting for pipeline transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 38-55.
    19. Li Zhu & Yeming Gong & Yishui Xu & Jun Gu, 2019. "Emergency Relief Routing Models for Injured Victims Considering Equity and Priority," Post-Print hal-02879681, HAL.
    20. Perumal, Shyam S.G. & Lusby, Richard M. & Larsen, Jesper, 2022. "Electric bus planning & scheduling: A review of related problems and methodologies," European Journal of Operational Research, Elsevier, vol. 301(2), pages 395-413.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:307:y:2023:i:3:p:1103-1116. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.