交通运输系统工程与信息

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (4): 241-253.DOI: 10.16097/j.cnki.1009-6744.2025.04.022

• 系统工程理论与方法 • 上一篇    下一篇

城际与市域铁路过轨运输下列车时刻表和停站方案协同优化

陈喜春，杨阳，田小鹏*   

  1. 兰州交通大学，交通运输学院，兰州730070
  • 收稿日期:2025-03-31 修回日期:2025-07-14 接受日期:2025-07-18 出版日期:2025-08-25 发布日期:2025-08-25
  • 作者简介:陈喜春(1979—)，男，吉林长春人，副教授，博士。
  • 基金资助:
    甘肃省自然科学基金(25JRRA142, 25JRRA1163)

Collaborative Optimization of Train Timetabling and Stop Planning for Intercity and Suburban Railways in Cross-line Operations

CHEN Xichun,YANG Yang,TIAN Xiaopeng*   

  1. School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China
  • Received:2025-03-31 Revised:2025-07-14 Accepted:2025-07-18 Online:2025-08-25 Published:2025-08-25
  • Supported by:
    Natural Science Foundation of Gansu Province, China (25JRRA142, 25JRRA1163)

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摘要： 在城际与市域铁路过轨运输模式下，协同优化列车时刻表和停站方案，有利于降低旅客换乘频次，提升旅客出行质量。首先，采用小时OD(Origin-Destination)客流作为旅客出行需求输入，通过列车候选停站方案反映过轨运输模式下可能的停站选择，借助时空网络分别引入基于弧段的列车与客流变量，建立多商品流约束刻画列车运行轨迹和旅客出行过程，采用耦合约束实现列车与客流的时空匹配，构建以最小化列车运行成本和旅客出行成本为目标的混合整数线性规划模型；其次，在拉格朗日松弛框架下，将所建模型分解为列车时空路径、停站方案选择和客流需求分配这3个易求解的子问题，设计基于对偶解的启发式方法求解原问题可行解；最后，为验证所提方法的有效性，以两组实际线路为背景进行案例分析。研究结果表明：本文方法能够生成响应旅客需求的列车服务方案，其中，超过80%跨线客流选择直达列车提升出行顺畅性，同时，各OD对的列车停站次数与客流分布趋势基本一致；对于17个车站和80列列车的案例，本文方法能够在合理计算时间内获得优于求解器的解。

关键词: 铁路运输, 列车时刻表, 时空网络, 停站方案, 拉格朗日松弛

Abstract: Under the cross-line operation mode of intercity and suburban railways, the collaborative optimization of train timetabling and train stop planning can reduce passenger transfers and enhance travel quality. First, this study considered the hour dependent origin-destination passenger flow as the input of demand, and used candidate stopping patterns to reflect the possible train stops under the cross-line mode. With the help of space-time network representations, the arc-based variables to address train running and passenger travel were introduced respectively. Then, multi-commodity flow constraints were established to describe the train operation trajectory and the passenger travel process. Coupling constraints were used to achieve the space-time matching of train movements and passenger travel. A mixed-integer linear programming model was formulated to minimize train operating costs and passenger travel costs. Under the Lagrangian relaxation framework, the model can be decomposed into three tractable subproblems: train time-space path, stopping pattern selection and passenger demand assignment. Further, A heuristic method were designed based on dual solutions to obtain feasible solutions of the primal problem. Finally, two real-life numerical experiments were conducted to assess the efficiency and effectiveness of the proposed approach. The results show that the proposed approach can generate train service plans that effectively responds the demand of passengers. Specifically, more than 80% of cross-line passengers choose direct train services to improve the smoothness of travel. Moreover, the generated train stop patterns generally align with the passenger flow distribution at each OD pair. In a case with 17 stations and 80 trains, the proposed method can yield solutions superior to those obtained by the solver within a reasonable computation time.

Key words: railway transportation, train timetable, space-time network, train stop plan, Lagrangian relaxation

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