交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (2): 212-220.DOI: 10.16097/j.cnki.1009-6744.2026.02.020

• 系统工程理论与方法 • 上一篇    下一篇

考虑车场条件的城轨灵活编组多交路列车运行图优化

鲍薪宇,张琦* ,肖雅玲,李涛   

  1. 北京交通大学,交通运输学院,北京100044
  • 收稿日期:2025-09-23 修回日期:2025-10-30 接受日期:2025-10-30 出版日期:2026-04-25 发布日期:2026-04-20
  • 作者简介:鲍薪宇(2000—),男,山西太原人,博士生。
  • 基金资助:
    国家自然科学基金(72471023, 52372300)。

Urban Rail Transit Timetable Optimization with Flexible Train Compositions and Multiple Service Routes Under Depot Conditions

BAO Xinyu, ZHANG Qi*, XIAO Yaling, LI Tao   

  1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
  • Received:2025-09-23 Revised:2025-10-30 Accepted:2025-10-30 Online:2026-04-25 Published:2026-04-20
  • Supported by:
    National Natural Science Foundation of China (72471023, 52372300)。

摘要: 灵活编组与多交路结合的运行模式使城轨列车能够在特定时段和车站调整编组,实现运力动态优化。本文在考虑车场条件下,研究灵活编组多交路模式的列车运行图优化问题。综合考虑车站折返、列车接续和车场布局约束,以最小化系统总运营成本与乘客总等待时间为目标,根据客流需求和线路条件,灵活确定列车编组类型和折返方向、时间和次数,并同时实现列车时刻表与车底周转计划的一体化优化。本文构建的混合整数线性规划模型,可直接通过商业求解器进行求解。案例分析表明,灵活编组多交路模式能够更好地适应潮汐客流特征,有效满足客流需求,显著提升车底周转效率;相比不考虑灵活编组和不考虑多交路模式的场景,本文模式可使目标函数值分别降低39.0%和4.3%;增加车场配置有助于增强运输能力并生成更合理的列车运行计划;同时,考虑车底使用均衡性约束有助于提升计划的稳定性与连续性。上述结果表明,本文方法可为运输企业提供灵活、高效的运行计划编制决策支持。

关键词: 城市交通, 列车运行图, 混合整数线性规划, 灵活编组, 多交路, 多车场

Abstract: The integration of flexible train compositions and multiple service routes allows urban rail trains to dynamically adjust their compositions at specific timestamps and stations, optimizing transport capacity in real time. This study optimizes train timetables incorporating these strategies under depot constraints. Considering constraints on the turnaround operations, train circulations, and depot layouts, the model minimizes total operating costs and passenger waiting time by adaptively determining train compositions, as well as turnaround directions, timings, and frequencies based on passenger demand and infrastructure conditions. It jointly optimizes the train timetables and rolling stock circulation plans through a mixed-integer linear programming model that can be solved with commercial solvers. The case studies demonstrate that the proposed method accommodates tidal passenger flows, enhances rolling stock utilization, and reduces the objective function by 39.0% and 4.3% relative to scenarios without flexible train compositions and without multiple service routes, respectively. Enhanced depot configurations can further increase transport capacity and operational rationality, and balance constraints of rolling stock utilization can enhance plan stability and continuity. The method provides efficient and flexible decision support for operational planning.

Key words: urban transportation, train timetable, mixed-integer linear programming, flexible train compositions, multiple service routes, multiple depots

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