IDEAS home Printed from https://ideas.repec.org/r/eee/transb/v128y2019icp344-379.html
   My bibliography  Save this item

Solving cyclic train timetabling problem through model reformulation: Extended time-space network construct and Alternating Direction Method of Multipliers methods

Citations

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


Cited by:

  1. Congcong Zou & Hongxia Lv & Miaomiao Lv & Shaoquan Ni & Qinglun Zhong, 2025. "High-Level Implicit Enumerations for Quadratic Periodic Train Timetabling with Prioritized Cross-Line Operations," Mathematics, MDPI, vol. 13(13), pages 1-33, June.
  2. Chi, Jushang & He, Shiwei & Zhang, Yongxiang, 2024. "Improved ADMM-based approach for optimizing intercity express transportation networks: A novel dual decomposition strategy with partial retention of coupling constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
  3. Maël Guiraud & Yann Strozecki, 2024. "Scheduling periodic messages on a shared link without buffering," Journal of Scheduling, Springer, vol. 27(5), pages 461-484, October.
  4. Zhang, Yongxiang & Peng, Qiyuan & Lu, Gongyuan & Zhong, Qingwei & Yan, Xu & Zhou, Xuesong, 2022. "Integrated line planning and train timetabling through price-based cross-resolution feedback mechanism," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 240-277.
  5. Maciej Kruszyna, 2022. "NOAH as an Innovative Tool for Modeling the Use of Suburban Railways," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
  6. Lu, Jiawei & Nie, Qinghui & Mahmoudi, Monirehalsadat & Ou, Jishun & Li, Chongnan & Zhou, Xuesong Simon, 2022. "Rich arc routing problem in city logistics: Models and solution algorithms using a fluid queue-based time-dependent travel time representation," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 143-182.
  7. Zhan, Shuguang & Wong, S.C. & Shang, Pan & Peng, Qiyuan & Xie, Jiemin & Lo, S.M., 2021. "Integrated railway timetable rescheduling and dynamic passenger routing during a complete blockage," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 86-123.
  8. Han Zheng & Junhua Chen & Zhaocha Huang & Jianhao Zhu, 2022. "Joint Optimization of Multi-Cycle Timetable Considering Supply-to-Demand Relationship and Energy Consumption for Rail Express," Mathematics, MDPI, vol. 10(21), pages 1-29, November.
  9. 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.
  10. Reisch, Julian & Großmann, Peter & Pöhle, Daniel & Kliewer, Natalia, 2021. "Conflict resolving – A local search algorithm for solving large scale conflict graphs in freight railway timetabling," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1143-1154.
  11. Feng, Tao & Lusby, Richard M. & Zhang, Yongxiang & Peng, Qiyuan, 2024. "Integrating train service route design with passenger flow allocation for an urban rail transit line," European Journal of Operational Research, Elsevier, vol. 313(1), pages 146-170.
  12. Feng, Tao & Lusby, Richard M. & Zhang, Yongxiang & Tao, Siyu & Zhang, Bojian & Peng, Qiyuan, 2024. "A branch-and-price algorithm for integrating urban rail crew scheduling and rostering problems," Transportation Research Part B: Methodological, Elsevier, vol. 183(C).
  13. Jiang, Yangsheng & Huangfu, Junjie & Xiao, Guosheng & Zhang, Yongxiang & Yao, Zhihong, 2025. "Energy-efficient trajectory design of connected automated vehicles platoon: A unified modeling approach using space-time-speed grid networks," Energy, Elsevier, vol. 314(C).
  14. Niu, Jiaxin & Qiao, Ke & Zhao, Peng, 2025. "Reliability improvement of rolling stock planning with maintenance requirements for high-speed railway," Reliability Engineering and System Safety, Elsevier, vol. 259(C).
  15. 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.
  16. Yunfang Peng & Xuejiao Li & Shiyu Liao & Wangchao Liu & Beixin Xia, 2025. "Scheduling the Just-in-Time Delivery of Parts for Mixed-Model Assembly Lines Considering the Electrical Energy Consumption of an Automated Guided Vehicle Trolley," Sustainability, MDPI, vol. 17(1), pages 1-23, January.
  17. Su, Boyi & D’Ariano, Andrea & Su, Shuai & Wang, Zhikai & Tessitore, Marta Leonina & Tang, Tao, 2025. "A risk-averse two-stage stochastic programming approach for backup rolling stock allocation and metro train rescheduling under uncertain disturbances," Transportation Research Part B: Methodological, Elsevier, vol. 196(C).
  18. Yueyi Li & Xiaodong Zhang, 2025. "Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach," Mathematics, MDPI, vol. 13(8), pages 1-26, April.
  19. Reisch, Julian, 2020. "State of the art overview on automatic railway timetable generation and optimization," Discussion Papers 2020/20, Free University Berlin, School of Business & Economics.
  20. Martin-Iradi, Bernardo & Ropke, Stefan, 2022. "A column-generation-based matheuristic for periodic and symmetric train timetabling with integrated passenger routing," European Journal of Operational Research, Elsevier, vol. 297(2), pages 511-531.
  21. 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.
  22. Cacchiani, Valentina & Qi, Jianguo & Yang, Lixing, 2020. "Robust optimization models for integrated train stop planning and timetabling with passenger demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 1-29.
  23. Pan Shang & Yu Yao & Liya Yang & Lingyun Meng & Pengli Mo, 2021. "Integrated Model for Timetabling and Circulation Planning on an Urban Rail Transit Line: a Coupled Network-Based Flow Formulation," Networks and Spatial Economics, Springer, vol. 21(2), pages 331-364, June.
  24. Mo, Pengli & D’Ariano, Andrea & Yang, Lixing & Veelenturf, Lucas P. & Gao, Ziyou, 2021. "An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 283-321.
  25. 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).
  26. Wang, Entai & Yang, Lixing & Yin, Jiateng & Zhang, Jinlei & Gao, Ziyou, 2024. "Passenger-oriented rolling stock scheduling in the metro system with multiple depots: Network flow based approaches," Transportation Research Part B: Methodological, Elsevier, vol. 180(C).
  27. Chao Li & Jinjin Tang & Jun Zhang & Qingqing Zhao & Lingli Wang & Jian Li, 2023. "Integrated optimization of urban rail transit line planning, timetabling and rolling stock scheduling," PLOS ONE, Public Library of Science, vol. 18(5), pages 1-30, May.
  28. Polinder, G.-J. & Cacchiani, V. & Schmidt, M.E. & Huisman, D., 2020. "An iterative heuristic for passenger-centric train timetabling with integrated adaption times," ERIM Report Series Research in Management ERS-2020-006-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  29. 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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.