A general metro timetable rescheduling approach for the minimisation of the capacity loss after random line disruption

References

• Altazin, Estelle, Stéphane Dauzère-Pérès, François Ramond, and Sabine Tréfond. 2020. “A Multi-Objective Optimization-Simulation Approach for Real Time Rescheduling in Dense Railway Systems.” European Journal of Operational Research 286: 662–672. doi:10.1016/j.ejor.2020.03.034.
   Web of Science ®Google Scholar
• Blume, S., M. A. Cardin, and G. Sansavini. 2020. “Dynamic Disruption Simulation in Large-Scale Urban Rail Transit Systems.” Complex Systems Design & Management.
   Google Scholar
• Cacchiani, Valentina, Dennis Huisman, Martin Kidd, Leo Kroon, Paolo Toth, Lucas Veelenturf, and Joris Wagenaar. 2014. “An Overview of Recovery Models and Algorithms for Real-Time Railway Rescheduling.” Transportation Research Part B: Methodological 63: 15–37. doi:10.1016/j.trb.2014.01.009.
   Web of Science ®Google Scholar
• Chow, A. H. F., and A. Pavlides. 2018. “Cost Functions and Multi-Objective Timetabling of Mixed Train Services.” Transportation Research Part A: Policy and Practice 113: 335–356. doi:10.1016/j.tra.2018.04.027.
   Web of Science ®Google Scholar
• Gao, Yuan, Leo Kroon, Marie Schmidt, and Lixing Yang. 2016. “Rescheduling a Metro Line in an Over-Crowded Situation After Disruptions.” Transportation Research Part B: Methodological 93: 425–449. doi:10.1016/j.trb.2016.08.011.
   Web of Science ®Google Scholar
• Ghaemi, N., O. Cats, and R. M. P. Goverde. 2017. “A Microscopic Model for Optimal Train Short-Turnings During Complete Blockages.” Transportation Research Part B: Methodological 105: 423–437. doi:10.1016/j.trb.2017.10.002.
   Web of Science ®Google Scholar
• Ghaemi, N., O. Cats, and R. M. P. Goverde. 2018. “Macroscopic Multiple-Station Short-Turning Model in Case of Complete Railway Blockages.” Transportation Research Part C: Emerging Technologies 89: 113–132. doi:10.1016/j.trc.2018.02.006.
   Web of Science ®Google Scholar
• Hassannayebi, Erfan, Arman Sajedinejad, Ali Kardannia, Masoud Shakibayifar, Hossein Jafari, and Ehsan Mansouri. 2021. “Simulation-optimization Framework for Train Rescheduling in Rapid Rail Transit.” Transportmetrica B: Transport Dynamics 9: 343–375. doi:10.1080/21680566.2020.1854896.
   Web of Science ®Google Scholar
• Hassannayebi, E., A. Sajedinejad, and S. Mardani. 2016. “Disruption Management in Urban Rail Transit System: A Simulation Based Optimization Approach Handbook of Research on Emerging Innovations in Rail Transportation Engineering.” IGI Global, 420–450. doi:10.4018/978-1-5225-0084-1.ch018
   Google Scholar
• Huang, Yeran, Carlo Mannino, Lixing Yang, and Tao Tang. 2020. “Coupling Time-Indexed and Big-M Formulations for Real-Time Train Scheduling During Metro Service Disruptions.” Transportation Research Part B: Methodological 133: 38-61. doi:10.1016/j.trb.2019.12.005.
   Google Scholar
• Leng, N., Z. Liao, and F. Corman. 2020. “Role of Timetable, Rolling Stock Rescheduling, and Information Strategies to Passengers in Public Transport Disruptions.” Transportation Research Record: Journal of the Transportation Research Board 2674: 135–147. doi:10.1177/0361198120927000.
   Web of Science ®Google Scholar
• Long, S., X. Luan, and F. Corman. 2021. “Passenger-oriented Rescheduling of Trains and Rolling Stock for Handling Large Passenger Demand: Linearized Models with Train Capacity Constraint.” Transportmetrica B 9: 641–672. doi:10.1080/21680566.2021.1932638.
   Google Scholar
• Louwerse, I., and D. Huisman. 2014. “Adjusting a Railway Timetable in Case of Partial or Complete Blockades.” European Journal of Operational Research 235: 583–593. doi:10.1016/j.ejor.2013.12.020.
   Web of Science ®Google Scholar
• Meng, L., and X. Zhou. 2011. “Robust Single-Track Train Dispatching Model Under a Dynamic and Stochastic Environment: A Scenario-Based Rolling Horizon Solution Approach.” Transportation Research Part B: Methodological 45: 1080–1102. doi:10.1016/j.trb.2011.05.001.
   Web of Science ®Google Scholar
• Peng, S., X. Yang, H. Wang, H. Dong, B. Ning, H. Tang, Z. Ying, and R. Tang. 2019. “Dispatching High-Speed Rail Trains via Utilizing the Reverse Direction Track: Adaptive Rescheduling Strategies and Application.” Sustainability 11. doi:10.3390/su11082351.
   Web of Science ®Google Scholar
• Puong, A., and N. H. Wilson. 2008. “A Train Holding Model for Urban Rail Transit Systems.” In Computer-Aided Systems in Public Transport, 319–337. Springer. doi:10.1007/978-3-540-73312-6_16.
   Google Scholar
• Samà, Marcella, Andrea D'Ariano, Francesco Corman, and Dario Pacciarelli. 2017. “A Variable Neighbourhood Search for Fast Train Scheduling and Routing During Disturbed Railway Traffic Situations.” Computers & Operations Research 78: 480–499. doi:10.1016/j.cor.2016.02.008.
   Web of Science ®Google Scholar
• Sameni, M. K., and A. Moradi. 2022. “Railway Capacity: A Review of Analysis Methods.” Journal of Rail Transport Planning & Management 24: 100357. doi:10.1016/j.jrtpm.2022.100357.
   Web of Science ®Google Scholar
• Schön, C., and E. König. 2018. “A Stochastic Dynamic Programming Approach for Delay Management of a Single Train Line.” European Journal of Operational Research 271: 501–518. doi:10.1016/j.ejor.2018.05.031.
   Web of Science ®Google Scholar
• UIC, Paris. 2004. “France,“Capacity,” UIC Code 406.” International Union of Railways.
   Google Scholar
• UIC, Code. 2013. “406: capacity.” International Union of Railways, Paris.
   Google Scholar
• Veelenturf Lucas, P., P. Kidd Martin, Valentina Cacchiani, G. Kroon Leo, and Paolo Toth. 2016. “A Railway Timetable Rescheduling Approach for Handling Large-Scale Disruptions.” Transportation Science 50: 841–862. doi:10.1287/trsc.2015.0618.
   Web of Science ®Google Scholar
• Xu, Peijuan, Francesco Corman, Qiyuan Peng, and Xiaojie Luan. 2017. “A Train Rescheduling Model Integrating Speed Management During Disruptions of High-Speed Traffic Under a Quasi-Moving Block System.” Transportation Research Part B: Methodological 104: 638–666. doi:10.1016/j.trb.2017.05.008.
   Web of Science ®Google Scholar
• Xu, X., K. Li, and L. Yang. 2016. “Rescheduling Subway Trains by a Discrete Event Model Considering Service Balance Performance.” Applied Mathematical Modelling 40: 1446–1466. doi:10.1016/j.apm.2015.06.031.
   Web of Science ®Google Scholar
• Yin, Jiateng, Tao Tang, Lixing Yang, Ziyou Gao, and Bin Ran. 2016. “Energy-efficient Metro Train Rescheduling with Uncertain Time-Variant Passenger Demands: An Approximate Dynamic Programming Approach.” Transportation Research Part B: Methodological 91: 178–210. doi:10.1016/j.trb.2016.05.009.
   Web of Science ®Google Scholar
• Zhan, Shuguang, Leo G. Kroon, Lucas P. Veelenturf, and Joris C. Wagenaar. 2015. “Real-time High-Speed Train Rescheduling in Case of a Complete Blockage.” Transportation Research Part B: Methodological 78: 182–201. doi:10.1016/j.trb.2015.04.001.
   Web of Science ®Google Scholar
• Zhan, Shuguang, Leo G. Kroon, Jun Zhao, and Qiyuan Peng. 2016. “A Rolling Horizon Approach to the High Speed Train Rescheduling Problem in Case of a Partial Segment Blockage.” Transportation Research Part E: Logistics and Transportation Review 95: 32–61. doi:10.1016/j.tre.2016.07.015.
   Web of Science ®Google Scholar
• Zhang, Shuyang, Hong K. Lo, Ka Fai Ng, and Guojun Chen. 2020. “Metro System Disruption Management and Substitute bus Service: A Systematic Review and Future Directions.” Transport Reviews 41: 230–251. doi:10.1080/01441647.2020.1834468.
   Web of Science ®Google Scholar
• Zhu, Y., and R. M. Goverde. 2020. “Integrated Timetable Rescheduling and Passenger Reassignment During Railway Disruptions.” Transportation Research Part B: Methodological 140: 282–314. doi:10.1016/j.trb.2020.09.001.
   Web of Science ®Google Scholar