IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v180y2023ics1366554523003241.html
   My bibliography  Save this article

Integrated optimization for high-speed railway express system with multiple modes

Author

Listed:
  • Zhen, Lu
  • Zhang, Nianzu
  • Yang, Zhiyuan

Abstract

High-speed railway (HSR) express, as an emerging transport option in the logistics industry, provides sufficient transport resources to satisfy the demands for large-scale, high value-added, and customized logistics requirements. Unlike conventional transport options, the HSR express is capable of using multiple modes (i.e., piggybacking, reserved-coach, and freight trains modes) to efficiently convey freights to a broad variety of locations. Based on the operational characteristics of various HSR express modes, this study takes into consideration of integrated optimization problems, such as whether high-speed trains of various HSR express modes can transport the freights of specific types, the amounts of freights transported by each HSR express mode, and the arrangement of capacity resources of each mode. This study establishes a stochastic mixed integer programming model with the goal of maximizing the net profit of the HSR express system and designs a heuristic solution approach to solve the model efficiently. To verify the validity of the proposed model and algorithm, a large number of numerical experiments and a real-world case are conducted. Based on the extensive experiments, this study provides railway companies potentially with useful insights for developing the HSR express with various modes.

Suggested Citation

  • Zhen, Lu & Zhang, Nianzu & Yang, Zhiyuan, 2023. "Integrated optimization for high-speed railway express system with multiple modes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
  • Handle: RePEc:eee:transe:v:180:y:2023:i:c:s1366554523003241
    DOI: 10.1016/j.tre.2023.103336
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554523003241
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2023.103336?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. Jinfei Wu & Xinghua Shan & Jingxia Sun & Shengyuan Weng & Shuo Zhao, 2023. "Daily Line Planning Optimization for High-Speed Railway Lines," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    2. 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).
    3. Pazour, Jennifer A. & Meller, Russell D. & Pohl, Letitia M., 2010. "A model to design a national high-speed rail network for freight distribution," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(3), pages 119-135, March.
    4. Zhen, Lu & Fan, Tianyi & Li, Haolin & Wang, Shuaian & Tan, Zheyi, 2023. "An optimization model for express delivery with high-speed railway," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 176(C).
    5. 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.
    6. 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.
    7. Li, Siqiao & Zhu, Xiaoning & Shang, Pan & Li, Tianqi & Liu, Wenqian, 2023. "Optimizing a shared freight and passenger high-speed railway system: A multi-commodity flow formulation with Benders decomposition solution approach," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 1-31.
    8. Xie, Fengjie & Ma, Mengdi & Ren, Cuiping, 2022. "Research on multilayer network structure characteristics from a higher-order model: The case of a Chinese high-speed railway system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    9. Canca, David & De-Los-Santos, Alicia & Laporte, Gilbert & Mesa, Juan A., 2019. "Integrated Railway Rapid Transit Network Design and Line Planning problem with maximum profit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 1-30.
    10. Zhang, Qin & Lusby, Richard Martin & Shang, Pan & Zhu, Xiaoning, 2022. "A heuristic approach to integrate train timetabling, platforming, and railway network maintenance scheduling decisions," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 210-238.
    11. Bi, Mingkai & He, Shiwei & Xu, Wangtu (Ato), 2019. "Express delivery with high-speed railway: Definitely feasible or just a publicity stunt," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 165-187.
    12. Xueqiao Yu & Lingyun Zhou & Mingkun Huo & Xiao Yu, 2021. "Research on High-Speed Railway Freight Train Organization Method considering Different Transportation Product Demands," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-17, July.
    13. Zeyu Wang & Leishan Zhou & Bin Guo & Xing Chen & Hanxiao Zhou, 2021. "An Efficient Hybrid Approach for Scheduling the Train Timetable for the Longer Distance High-Speed Railway," Sustainability, MDPI, vol. 13(5), pages 1-22, February.
    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. Zhang, Yundi & Hu, Rong & Chen, Ruotian & Cai, Dong-ling & Jiang, Changmin, 2024. "Competition in cargo and passenger between high-speed rail and airlines—considering the vertical structure of transportation," Transport Policy, Elsevier, vol. 151(C), pages 120-133.
    2. Yi Liu & Senbin Yu & Chaoyang Zhang & Peiran Zhang & Yang Wang & Liang Gao, 2022. "Critical Percolation on Temporal High-Speed Railway Networks," Mathematics, MDPI, vol. 10(24), pages 1-8, December.
    3. Zhengwen Liao, 2023. "Rescheduling Out-of-Gauge Trains with Speed Restrictions and Temporal Blockades on the Opposite-Direction Track," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
    4. Li, Siqiao & Zhu, Xiaoning & Shang, Pan & Li, Tianqi & Liu, Wenqian, 2023. "Optimizing a shared freight and passenger high-speed railway system: A multi-commodity flow formulation with Benders decomposition solution approach," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 1-31.
    5. Hanlin Gao & Meiqing Zhang & Anne Goodchild, 2020. "Empirical Analysis of Relieving High-Speed Rail Freight Congestion in China," Sustainability, MDPI, vol. 12(23), pages 1-16, November.
    6. 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).
    7. Ji, Hangyu & Wang, Rui & Zhang, Chuntian & Yin, Jiateng & Ma, Lin & Yang, Lixing, 2024. "Optimization of train schedule with uncertain maintenance plans in high-speed railways: A stochastic programming approach," Omega, Elsevier, vol. 124(C).
    8. Yidong Wang & Rui Song & Shiwei He & Zilong Song, 2022. "Train Routing and Track Allocation Optimization Model of Multi-Station High-Speed Railway Hub," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    9. Xu, Zhandong & Xie, Jun & Liu, Xiaobo & Nie, Yu (Marco), 2020. "Hyperpath-based algorithms for the transit equilibrium assignment problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    10. Limsawasd, Charinee & Athigakunagorn, Nathee & Khathawatcharakun, Phattadon & Boonmee, Atiwat, 2022. "Skip-Stop Strategy Patterns optimization to enhance mass transit operation under physical distancing policy due to COVID-19 pandemic outbreak," Transport Policy, Elsevier, vol. 126(C), pages 225-238.
    11. Mahmoud Owais & Abdou S. Ahmed & Ghada S. Moussa & Ahmed A. Khalil, 2020. "An Optimal Metro Design for Transit Networks in Existing Square Cities Based on Non-Demand Criterion," Sustainability, MDPI, vol. 12(22), pages 1-28, November.
    12. Gkiotsalitis, K. & Cats, O. & Liu, T. & Bult, J.M., 2023. "An exact optimization method for coordinating the arrival times of urban rail lines at a common corridor," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 178(C).
    13. Hartleb, Johann & Schmidt, Marie, 2022. "Railway timetabling with integrated passenger distribution," European Journal of Operational Research, Elsevier, vol. 298(3), pages 953-966.
    14. Li, Siqiao & Zhu, Xiaoning & Shang, Pan & Wang, Li & Li, Tianqi, 2024. "Scheduling shared passenger and freight transport for an underground logistics system," Transportation Research Part B: Methodological, Elsevier, vol. 183(C).
    15. Li, Guoyuan & Chen, Anthony, 2022. "Frequency-based path flow estimator for transit origin-destination trip matrices incorporating automatic passenger count and automatic fare collection data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    16. Saleh, Ali & Remenyte-Prescott, Rasa & Prescott, Darren & Chiachío, Manuel, 2024. "Intelligent and adaptive asset management model for railway sections using the iPN method," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    17. Zhang, Huimin & Li, Shukai & Wang, Yihui & Yang, Lixing & Gao, Ziyou, 2021. "Collaborative real-time optimization strategy for train rescheduling and track emergency maintenance of high-speed railway: A Lagrangian relaxation-based decomposition algorithm," Omega, Elsevier, vol. 102(C).
    18. Fragkos, Ioannis & Cordeau, Jean-François & Jans, Raf, 2021. "Decomposition methods for large-scale network expansion problems," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 60-80.
    19. Hu, Wanjie & Dong, Jianjun & Hwang, Bon-Gang & Ren, Rui & Chen, Zhilong, 2022. "Is mass rapid transit applicable for deep integration of freight-passenger transport? A multi-perspective analysis from urban China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 490-510.
    20. SteadieSeifi, M. & Dellaert, N.P. & Nuijten, W. & Van Woensel, T. & Raoufi, R., 2014. "Multimodal freight transportation planning: A literature review," European Journal of Operational Research, Elsevier, vol. 233(1), pages 1-15.

    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:transe:v:180:y:2023:i:c:s1366554523003241. 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/wps/find/journaldescription.cws_home/600244/description#description .

    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.