IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v238y2014i3p863-875.html
   My bibliography  Save this article

An implicit enumeration algorithm for the passenger service planning problem: Application to the Taiwan Railways Administration line

Author

Listed:
  • Lin, Dung-Ying
  • Ku, Yu-Hsiung

Abstract

In a passenger railroad system, the service planning problem determines the train stopping strategy, taking into consideration multiple train classes and customer origin–destination (OD) demand, to maximize the short-term operational profit of a rail company or the satisfaction levels of the passengers. The service plan is traditionally decided by rule of thumb, an approach that leaves much room for improvement. To systematically analyze this problem, we propose an integer program approach to determine the optimal service plan for a rail company. The formulated problem has a complex solution space, and commonly used commercial optimization packages are currently incapable of solving this problem efficiently, especially when problems of realistic sizes are considered. Therefore, we develop an implicit enumeration algorithm that incorporates intelligent branching and effective bounding strategies so that the solution space of this integer program can be explored efficiently. The numerical results show that the proposed implicit enumeration algorithm can solve real-world problems and can obtain service plans that are at least as good as those developed by the rail company.

Suggested Citation

  • Lin, Dung-Ying & Ku, Yu-Hsiung, 2014. "An implicit enumeration algorithm for the passenger service planning problem: Application to the Taiwan Railways Administration line," European Journal of Operational Research, Elsevier, vol. 238(3), pages 863-875.
  • Handle: RePEc:eee:ejores:v:238:y:2014:i:3:p:863-875
    DOI: 10.1016/j.ejor.2014.04.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221714003518
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2014.04.025?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. Mussone, Lorenzo & Wolfler Calvo, Roberto, 2013. "An analytical approach to calculate the capacity of a railway system," European Journal of Operational Research, Elsevier, vol. 228(1), pages 11-23.
    2. Twan Dollevoet & Dennis Huisman & Marie Schmidt & Anita Schöbel, 2012. "Delay Management with Rerouting of Passengers," Transportation Science, INFORMS, vol. 46(1), pages 74-89, February.
    3. Marshall L. Fisher, 1981. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 27(1), pages 1-18, January.
    4. Mitrovic-Minic, Snezana & Krishnamurti, Ramesh & Laporte, Gilbert, 2004. "Double-horizon based heuristics for the dynamic pickup and delivery problem with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 38(8), pages 669-685, September.
    5. Chang, Yu-Hern & Yeh, Chung-Hsing & Shen, Ching-Cheng, 2000. "A multiobjective model for passenger train services planning: application to Taiwan's high-speed rail line," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 91-106, February.
    6. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    7. Lee, Yusin & Chen, Chuen-Yih, 2009. "A heuristic for the train pathing and timetabling problem," Transportation Research Part B: Methodological, Elsevier, vol. 43(8-9), pages 837-851, September.
    8. Assad, Arjang A., 1980. "Modelling of rail networks: Toward a routing/makeup model," Transportation Research Part B: Methodological, Elsevier, vol. 14(1-2), pages 101-114.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pu, Song & Zhan, Shuguang, 2021. "Two-stage robust railway line-planning approach with passenger demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    2. Tian, Xiaopeng & Niu, Huimin, 2020. "Optimization of demand-oriented train timetables under overtaking operations: A surrogate-dual-variable column generation for eliminating indivisibility," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 143-173.
    3. Xin Zhang & Lei Nie & Xin Wu & Yu Ke, 2020. "How to Optimize Train Stops under Diverse Passenger Demand: a New Line Planning Method for Large-Scale High-Speed Rail Networks," Networks and Spatial Economics, Springer, vol. 20(4), pages 963-988, December.
    4. Salvatore Antonio Biancardo & Francesco Avella & Ernesto Di Lisa & Xinqiang Chen & Francesco Abbondati & Gianluca Dell’Acqua, 2021. "Multiobjective Railway Alignment Optimization Using Ballastless Track and Reduced Cross-Section in Tunnel," Sustainability, MDPI, vol. 13(19), pages 1-19, September.
    5. Zilong Fan & Di Liu & Wenyu Rong & Chengrui Li, 2022. "A Multi-Objective Optimization Model for the Intercity Railway Train Operation Plan: The Case of Beijing-Xiong’an ICR," Sustainability, MDPI, vol. 14(14), pages 1-18, July.

    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. Sparing, Daniel & Goverde, Rob M.P., 2017. "A cycle time optimization model for generating stable periodic railway timetables," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 198-223.
    2. Qi, Jianguo & Yang, Lixing & Di, Zhen & Li, Shukai & Yang, Kai & Gao, Yuan, 2018. "Integrated optimization for train operation zone and stop plan with passenger distributions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 151-173.
    3. Lee, Yusin & Lu, Li-Sin & Wu, Mei-Ling & Lin, Dung-Ying, 2017. "Balance of efficiency and robustness in passenger railway timetables," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 142-156.
    4. Tian, Xiaopeng & Niu, Huimin, 2020. "Optimization of demand-oriented train timetables under overtaking operations: A surrogate-dual-variable column generation for eliminating indivisibility," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 143-173.
    5. Schön, Cornelia & König, Eva, 2018. "A stochastic dynamic programming approach for delay management of a single train line," European Journal of Operational Research, Elsevier, vol. 271(2), pages 501-518.
    6. Ruf, Moritz & Cordeau, Jean-François, 2021. "Adaptive large neighborhood search for integrated planning in railroad classification yards," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 26-51.
    7. Hassini, Elkafi & Verma, Manish, 2016. "Disruption risk management in railroad networks: An optimization-based methodology and a case studyAuthor-Name: Azad, Nader," Transportation Research Part B: Methodological, Elsevier, vol. 85(C), pages 70-88.
    8. Nie, Wei & Li, Hao & Xiao, Na & Yang, Hao & Jiang, Zhishu & Buhigiro, Nsabimana, 2021. "Modeling and solving the last-shift period train scheduling problem in subway networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    9. David Schindl & Nicolas Zufferey, 2015. "A learning tabu search for a truck allocation problem with linear and nonlinear cost components," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(1), pages 32-45, February.
    10. Zhang, Chuntian & Gao, Yuan & Yang, Lixing & Gao, Ziyou & Qi, Jianguo, 2020. "Joint optimization of train scheduling and maintenance planning in a railway network: A heuristic algorithm using Lagrangian relaxation," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 64-92.
    11. Maosheng Li & Zhengqiu Liu & Yonghong Zhang & Weijun Liu & Feng Shi, 2017. "Distribution analysis of train interval journey time employing the censored model with shifting character," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(4), pages 715-733, March.
    12. Corman, Francesco & D’Ariano, Andrea & Marra, Alessio D. & Pacciarelli, Dario & Samà, Marcella, 2017. "Integrating train scheduling and delay management in real-time railway traffic control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 213-239.
    13. Cacchiani, Valentina & Furini, Fabio & Kidd, Martin Philip, 2016. "Approaches to a real-world Train Timetabling Problem in a railway node," Omega, Elsevier, vol. 58(C), pages 97-110.
    14. Vansteenwegen, Pieter & Dewilde, Thijs & Burggraeve, Sofie & Cattrysse, Dirk, 2016. "An iterative approach for reducing the impact of infrastructure maintenance on the performance of railway systems," European Journal of Operational Research, Elsevier, vol. 252(1), pages 39-53.
    15. Eva König, 2020. "A review on railway delay management," Public Transport, Springer, vol. 12(2), pages 335-361, June.
    16. Jiang, Feng & Cacchiani, Valentina & Toth, Paolo, 2017. "Train timetabling by skip-stop planning in highly congested lines," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 149-174.
    17. Repolho, Hugo M. & Church, Richard L. & Antunes, António P., 2016. "Optimizing station location and fleet composition for a high-speed rail line," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 437-452.
    18. Xu, Xiaoming & Li, Keping & Yang, Lixing, 2015. "Scheduling heterogeneous train traffic on double tracks with efficient dispatching rules," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 364-384.
    19. Zhang, Chuntian & Gao, Yuan & Cacchiani, Valentina & Yang, Lixing & Gao, Ziyou, 2023. "Train rescheduling for large-scale disruptions in a large-scale railway network," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    20. Dauzère-Pérès, Stéphane & De Almeida, David & Guyon, Olivier & Benhizia, Faten, 2015. "A Lagrangian heuristic framework for a real-life integrated planning problem of railway transportation resources," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 138-150.

    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:238:y:2014:i:3:p:863-875. 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.