Integrated Optimisation of Train Timetables and Maintenance Windows under Mixed Passenger and Freight Train Operation Mode
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The train timetable and maintenance windows are closely interrelated and mutually constrained, creating a coupled relationship. Optimising the train timetable can greatly enhance the operational efficiency of trains. This study focuses on the mixed passenger-freight train operation mode and investigates the integrated optimisation of train timetables and maintenance windows in this context. The problem is modelled as a multi-objective mixed-integer programming problem. The model’s objectives are twofold: to minimise the total travel time of all trains and to maximise the density of train paths. Several constraints are incorporated, including those related to train stopping, train safety intervals, passenger train departure time windows and maintenance windows. These constraints ensure that the model reflects practical operational requirements while achieving optimal efficiency. The model places particular emphasis on station capacity constraints. To facilitate solving, these constraints are linearised. A case study is conducted to compare scenarios with and without considering station capacity constraints. The results demonstrate the effectiveness of the proposed model. This study provides theoretical support for the integrated optimisation of train timetables and maintenance windows under mixed passenger-freight train operation mode and offers valuable insights for improving the efficiency of railway transportation.
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Jiang F, et al. Large scale freight train diagram optimization heuristic algorithm based on lagrangian relaxation. Journal of the China Railway Society. 2020;42(03):21-31. DOI: 10.3969/j.issn.1001-8360.2020.03.003.
Yang L, et al. Collaborative optimization of last-train timetables with accessibility: A space-time network design based approach. Transportation Research Part C: Emerging Technologies. 2020;114: 572-597. DOI: org/10.1016/jtrc.2020.02.022.
Zhang T, et al. Linear programming collaborative optimization model on operation of over-night train and setting of maintenance time window. Journal of the China Railway Society. 1-13[2025-1-3].
Zhang M, et al. Coordinated optimization of train timetable and maintenance skylight considering Pareto optimality. Journal of Railway Science and Engineering. 2024;21(03):949-958. DOI: 10.19713/j.cnki.43-1423/u.T20230820.
Lan Z, et al. Optimization for double track railway train timetabling considering the maintenance skylight and the number of arrival departure tracks. Journal of Beijing Jiaotong University. 2018;42(03):30-36. DOI: 10.11860/j.issn.1673-0291.2018.03.005.
Yang K, et al. Co-optimization between maintenance curfew and overnight train plan in high speed railway. Journal of the China Railway Society. 2015;37(04):1-7. DOI: 10,3969/j.issn.1001-8360.2015.04.001.
Mu C, et al. Integrated optimization model on maintenance time window and train timetabling. Journal of Railway Science and Engineering. 2018;15(08):2155-2162. DOI:10.19713/j.cnki.43-1423/u.2018.08.032.
Li D, et al. Combinatorial optimization of service order and overtaking for demand‐oriented timetabling in a Single Railway Line. Journal of Advanced Transportation. 2018;1 (2018): 4613468. DOI: 10.1155/2018/4613468.
Liu M, et al. Study on optimization of night train operation and maintenance window configuration of high-speed railway. Railway Transport and Economy. 2015;37(11):22-25+88. DOI: 10.16668/j.cnki.issn.1003-1421.2015.11.05.
Ping Q, et al. Organization methods of overnight operation for Chinese high-speed railways. Journal of Southwest Jiaotong University. 2015; 50(4): 569−576. DOI: 10.3969/j.issn.0258-2724.2015.04.001.
Boland N, et al. Scheduling arc maintenance jobs in a network to maximize total flow over time. Discrete Applied Mathematics. 2014; 163(1): 34−52. DOI:10.1016/j.cor.2015.05.011.
Zhang C, et al. Joint optimization of train scheduling and maintenance planning in a railway network: a heuristic algorithm using lagrangian relaxation. Transportation Research Part B. 2020;134:64-92. DOI: 10.1016/j.trb.2020.02.008.
Lidén T, et al. Resource considerations for integrated planning of railway traffic and maintenance windows. Journal of rail transport planning & management. 2018;8(1): 1-15. DOI: 10.1016/j.jrtpm.2018.02.001.
Yang X, et al. Bi-objective programming approach for solving the metro timetable optimization problem with dwell time uncertainty. Transportation Research Part E: Logistics and Transportation Review 97 (2017): 22-37. DOI: 10.1016/j.tre.2016.10.012.
Xu C, et al. Collaborative optimization for timetable and maintenance window based on two-stage algorithm. Journal of Southwest Jiaotong University. 2020;55(04):882-888. DOI: 10.3969/j.issn.0258-2724.20180577.
Yang H, et al. Variable neighborhood search and alternating direction method of multipliers for integrated optimization of maintenance windows and train timetables. IEEE Transactions on Intelligent Transportation Systems(2024). DOI: 10.1109/TITS.2024.3432672.
Yang H, et al. Integrated robust optimization of maintenance windows and train timetables using admm-driven and nested simulation heuristic algorithm. Transportation Research Part C: Emerging Technologies 160 (2024): 104526. DOI: 10.1016/j.trc.2024.104526.
Zhang Y, et al. Microscopic optimization model and algorithm for integrating train timetabling and track maintenance task scheduling. Transportation Research Part B: Methodological. 2019;127: 237-278. DOI: 10.1016/j.trb.2019.07.010.
Zhao H, et al. A method for robust train diagram generation based on improved particle swarm optimization algorithm. China Railway Science. 2013;34(03):116-121. DOI:1001-4632(2013)03-0116-06.
Ni S, et al. Optimization study of group plan on double-track heavy-haul railways based on group train operation. Journal of Railway Science and Engineering.2024;1-14. DOI: 10.19713/j.cnki.43-1423/u.T20241275.
Guo X, et al. Multiperiod-based timetable optimization for metro transit networks. Transportation Research Part B: Methodological. 2017;96: 46-67. DOI: 10.1016/j.trb.2016.11.005.
Meng X, et al. A petri net model of train operation simulation for harmonizing train timetables of neighbor dispatching sections. Promet-Traffic&Transportation. 2018; 30(6): 647-660. DOI: 10.7307/ptt.v30i6.2713.
XU X, et al. Integrated train timetabling and locomotive assignment. Transportation Research Part B. 2018; DOI: 117.10.1016/j.trb.2018.09.015.
Shi F, et al. A timing-cycle iterative optimizing method for drawing single-track railway train diagrams. Journal of the China Railway Society. 2005;(01):1-5.
Yang L, et al. Collaborative optimization for train scheduling and train stop planning on high-speed railways. Omega.2016; 64: 57-76. DOI: 10.1016/j.omega.2015.11.003.
Wang, Y, et al. Integrated timetable synchronization optimization with capacity constraint under time-dependent demand for a rail transit network. Computers & Industrial Engineering. 142 (2020): 106374. DOI: 10.1016/j.cie.2020.106374.
Mi L, et al. Integrated optimization of the train timetable and freight allocation on shared freight and passenger high-speed railway system. Control and Decision.1-9[2024-10-24]. DOI: 10.13195/j.kzyjc.2023.1749.
Li, D, et al. Integrated optimization of flexible train timetable, stop plan and exogenous passenger assignment under demand responsive condition. Journal of Intelligent Transportation Systems. 2024;1-28. DOI: 10.1080/15472450.2024.2438818.
Copyright (c) 2026 Weigang YUE, Haijun LI, Ruhu GAO, Xiaoyang ZHANG

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