IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i6p1418-d1097948.html
   My bibliography  Save this article

A Lagrangian Method for Calculation of Passing Capacity on a Railway Hub Station

Author

Listed:
  • Lu Yang

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Leishan Zhou

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Hanxiao Zhou

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Chang Han

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Wenqiang Zhao

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

Abstract

This research paper proposes a Lagrangian method to address the passing capacity of the calculation problem (PCCP) for a hub station in a high-speed railway (HSR) system. The passing capacity of a hub station is critical for determining the train timetable and maximizing the number of trains that can operate on different lines. The objective of this study is to determine the maximum number of trains that can pass through, start at, or end at a hub station. To achieve this objective, a mathematical model was introduced to solve the PCCP. The model was decomposed into two parts using a Lagrangian relaxation algorithm. The first part of the model was a simple train arrival problem (TAP) that reflected the timing of trains at the hub station with simultaneous arrival and departure time constraints. The second part of the model was a train spatio-temporal routing problem (TSRP) that aimed to solve the shortest spatio-temporal path of trains with free conflict with the train’s trajectory. A real instance was provided to demonstrate the feasibility of the proposed approach and the effectiveness of the Lagrangian method. The results showed that the proposed method can efficiently solve the PCCP and maximize the passing capacity of a hub station in an HSR system.

Suggested Citation

  • Lu Yang & Leishan Zhou & Hanxiao Zhou & Chang Han & Wenqiang Zhao, 2023. "A Lagrangian Method for Calculation of Passing Capacity on a Railway Hub Station," Mathematics, MDPI, vol. 11(6), pages 1-20, March.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:6:p:1418-:d:1097948
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/6/1418/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/6/1418/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Matthew E. H. Petering & Mojtaba Heydar & Dietrich R. Bergmann, 2016. "Mixed-Integer Programming for Railway Capacity Analysis and Cyclic, Combined Train Timetabling and Platforming," Transportation Science, INFORMS, vol. 50(3), pages 892-909, August.
    2. Zwaneveld, Peter J. & Kroon, Leo G. & van Hoesel, Stan P. M., 2001. "Routing trains through a railway station based on a node packing model," European Journal of Operational Research, Elsevier, vol. 128(1), pages 14-33, January.
    3. Ziyan Feng & Chengxuan Cao & Yutong Liu & Yaling Zhou, 2018. "A Multiobjective Optimization for Train Routing at the High-Speed Railway Station Based on Tabu Search Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-22, October.
    4. Igor Litvinchev & Edith L. Ozuna, 2012. "Lagrangian Bounds and a Heuristic for the Two-Stage Capacitated Facility Location Problem," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 1(1), pages 59-71, January.
    5. Zwaneveld, P.J. & Kroon, L.G. & van Hoesel, C.P.M., 1997. "Routing trains through a railway station based on a Node Packing model," Research Memorandum 030, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    6. Yuan, Jianxin & Hansen, Ingo A., 2007. "Optimizing capacity utilization of stations by estimating knock-on train delays," Transportation Research Part B: Methodological, Elsevier, vol. 41(2), pages 202-217, February.
    7. G. Caimi & F. Chudak & M. Fuchsberger & M. Laumanns & R. Zenklusen, 2011. "A New Resource-Constrained Multicommodity Flow Model for Conflict-Free Train Routing and Scheduling," Transportation Science, INFORMS, vol. 45(2), pages 212-227, May.
    8. Alberto Caprara & Matteo Fischetti & Paolo Toth, 1999. "A Heuristic Method for the Set Covering Problem," Operations Research, INFORMS, vol. 47(5), pages 730-743, October.
    9. Kroon, Leo G. & Edwin Romeijn, H. & Zwaneveld, Peter J., 1997. "Routing trains through railway stations: complexity issues," European Journal of Operational Research, Elsevier, vol. 98(3), pages 485-498, May.
    10. J. E. Beasley, 1990. "A lagrangian heuristic for set‐covering problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 37(1), pages 151-164, February.
    11. Tragantalerngsak, Suda & Holt, John & Ronnqvist, Mikael, 1997. "Lagrangian heuristics for the two-echelon, single-source, capacitated facility location problem," European Journal of Operational Research, Elsevier, vol. 102(3), pages 611-625, November.
    12. Peter J. Zwaneveld & Leo G. Kroon & H. Edwin Romeijn & Marc Salomon & Stéphane Dauzère-Pérès & Stan P. M. Van Hoesel & Harrie W. Ambergen, 1996. "Routing Trains Through Railway Stations: Model Formulation and Algorithms," Transportation Science, INFORMS, vol. 30(3), pages 181-194, August.
    13. Marshall L. Fisher & R. Jaikumar & Luk N. Van Wassenhove, 1986. "A Multiplier Adjustment Method for the Generalized Assignment Problem," Management Science, INFORMS, vol. 32(9), pages 1095-1103, September.
    14. Zhang, Jiamin, 2015. "Analysis on line capacity usage for China high speed railway with optimization approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 336-349.
    15. Liu, Yang & Wu, Fanyou & Lyu, Cheng & Li, Shen & Ye, Jieping & Qu, Xiaobo, 2022. "Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    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. Nikola Bešinović & Rob M. P. Goverde, 2019. "Stable and robust train routing in station areas with balanced infrastructure capacity occupation," Public Transport, Springer, vol. 11(2), pages 211-236, August.
    2. Jingliu Xu & Zhimei Wang & Shangjun Yao & Jiarong Xue, 2022. "Train Operations Organization in High-Speed Railway Station Considering Variable Configuration," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
    3. Jovanović, Predrag & Pavlović, Norbert & Belošević, Ivan & Milinković, Sanjin, 2020. "Graph coloring-based approach for railway station design analysis and capacity determination," European Journal of Operational Research, Elsevier, vol. 287(1), pages 348-360.
    4. Bhatia, Vinod & Sharma, Seema, 2021. "Expense based performance analysis and resource rationalization: Case of Indian Railways," Socio-Economic Planning Sciences, Elsevier, vol. 76(C).
    5. Richard Lusby & Jesper Larsen & David Ryan & Matthias Ehrgott, 2011. "Routing Trains Through Railway Junctions: A New Set-Packing Approach," Transportation Science, INFORMS, vol. 45(2), pages 228-245, May.
    6. Burdett, R.L. & Kozan, E., 2010. "A disjunctive graph model and framework for constructing new train schedules," European Journal of Operational Research, Elsevier, vol. 200(1), pages 85-98, January.
    7. Lu, Gongyuan & Nie, Yu(Marco) & Liu, Xiaobo & Li, Denghui, 2019. "Trajectory-based traffic management inside an autonomous vehicle zone," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 76-98.
    8. Alberto Caprara & Laura Galli & Paolo Toth, 2011. "Solution of the Train Platforming Problem," Transportation Science, INFORMS, vol. 45(2), pages 246-257, May.
    9. Dewilde, Thijs & Sels, Peter & Cattrysse, Dirk & Vansteenwegen, Pieter, 2014. "Improving the robustness in railway station areas," European Journal of Operational Research, Elsevier, vol. 235(1), pages 276-286.
    10. Twan Dollevoet & Dennis Huisman & Leo Kroon & Marie Schmidt & Anita Schöbel, 2015. "Delay Management Including Capacities of Stations," Transportation Science, INFORMS, vol. 49(2), pages 185-203, May.
    11. Wanqi Wang & Yun Bao & Sihui Long, 2022. "Rescheduling Urban Rail Transit Trains to Serve Passengers from Uncertain Delayed High-Speed Railway Trains," Sustainability, MDPI, vol. 14(9), pages 1-20, May.
    12. Pellegrini, Paola & Rodriguez, Joaquin, 2013. "Single European Sky and Single European Railway Area: A system level analysis of air and rail transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 57(C), pages 64-86.
    13. Burggraeve, Sofie & Vansteenwegen, Pieter, 2017. "Robust routing and timetabling in complex railway stations," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 228-244.
    14. Sels, P. & Vansteenwegen, P. & Dewilde, T. & Cattrysse, D. & Waquet, B. & Joubert, A., 2014. "The train platforming problem: The infrastructure management company perspective," Transportation Research Part B: Methodological, Elsevier, vol. 61(C), pages 55-72.
    15. Leonardo Lamorgese & Carlo Mannino & Mauro Piacentini, 2016. "Optimal Train Dispatching by Benders’-Like Reformulation," Transportation Science, INFORMS, vol. 50(3), pages 910-925, August.
    16. Delorme, Xavier & Gandibleux, Xavier & Rodriguez, Joaquín, 2009. "Stability evaluation of a railway timetable at station level," European Journal of Operational Research, Elsevier, vol. 195(3), pages 780-790, June.
    17. G. Caimi & F. Chudak & M. Fuchsberger & M. Laumanns & R. Zenklusen, 2011. "A New Resource-Constrained Multicommodity Flow Model for Conflict-Free Train Routing and Scheduling," Transportation Science, INFORMS, vol. 45(2), pages 212-227, May.
    18. Wang, Dian & D’Ariano, Andrea & Zhao, Jun & Zhong, Qingwei & Peng, Qiyuan, 2022. "Integrated rolling stock deadhead routing and timetabling in urban rail transit lines," European Journal of Operational Research, Elsevier, vol. 298(2), pages 526-559.
    19. Ortiz-Astorquiza, Camilo & Contreras, Ivan & Laporte, Gilbert, 2018. "Multi-level facility location problems," European Journal of Operational Research, Elsevier, vol. 267(3), pages 791-805.
    20. Andrea D'Ariano & Francesco Corman & Dario Pacciarelli & Marco Pranzo, 2008. "Reordering and Local Rerouting Strategies to Manage Train Traffic in Real Time," Transportation Science, INFORMS, vol. 42(4), pages 405-419, November.

    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:gam:jmathe:v:11:y:2023:i:6:p:1418-:d:1097948. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.