铁路长大坡道线路考虑维修天窗设置的列车运行图优化

doi:10.16097/j.cnki.1009-6744.2025.03.026

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (3): 288-298.DOI: 10.16097/j.cnki.1009-6744.2025.03.026

铁路长大坡道线路考虑维修天窗设置的列车运行图优化

田志强^*1a,1b，刘磊^1a,1b，孙国锋²，张俊峰^1a,1b，梁辉^1a

1. 兰州交通大学，a.交通运输学院，b.高原铁路运输智慧管控铁路行业重点实验室，兰州730070；2. 北京交通大学，交通运输学院，北京100044

收稿日期:2024-12-25 修回日期:2025-02-05 接受日期:2025-02-17 出版日期:2025-06-25 发布日期:2025-06-21
作者简介:田志强(1981—)，男，甘肃武威人，教授，博士。
基金资助:
国家自然科学基金(71761023, 72161023)；西部铁路智能运维与管控关键技术研究(24ZYQA044)。

Optimization of Train Operation Diagram Considering Maintenance Windows on Railway Lines with Long and Steep Gradients

TIAN Zhiqiang^*1a,1b, LIU Lei^1a,1b, SUN Guofeng², ZHANG Junfeng^1a,1b, LIANG Hui^1a

1a. School of Traffic and Transportation, 1b. Key Laboratory of Railway Industry on Plateau Railway Transportation Intelligent Management and Control, Lanzhou Jiaotong University, Lanzhou 730070, China; 2. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

Received:2024-12-25 Revised:2025-02-05 Accepted:2025-02-17 Online:2025-06-25 Published:2025-06-21
Supported by:
National Natural Science Foundation of China (71761023, 72161023)；Research on Key Technologies of Intelligent Operation and Maintenance and Control of Western Railway(24ZYQA044)。

摘要/Abstract

摘要： 在铁路长大坡道线路场景下，列车运行过程存在持续时间较长的牵引和制动阶段，通过充分考虑同一供电分区内牵引阶段与制动阶段列车工况重叠，能为列车节能运行提供有利条件。首先，基于长大坡道线路特点，分析列车到发时刻对工况重叠的影响；其次，为避免供电冲突，考虑同一供电分区维修天窗起止时刻相同，并综合考虑列车运行与维修天窗开设等约束，构建以列车工况重叠时间最大化，总旅行时间最小化为优化目标的混合整数规划模型，基于模型特点运用ε-约束法和GUROBI求解。最后，通过案例验证模型和算法的有效性。结果表明，本文设计的算法能有效求解案例，与优化前相比，列车总工况重叠时间增加了24.39%。研究成果能为长大坡道线路运输组织决策过程提供科学参考。

关键词: 铁路运输, 列车工况重叠时间, ε-约束法, 列车运行图, 维修天窗, 长大坡道

Abstract: In the context of railway lines with long and steep gradients, the train operation process involves traction and braking stages that last for a relatively long time. By fully considering the overlap of train working conditions between the traction stage and the braking stage within the same power supply section, favorable conditions can be provided for the energy-saving operation of trains. Firstly, based on the characteristics of long and steep gradient lines, the impact of train arrival and departure times on the overlap of working conditions is analyzed. Secondly, to avoid power supply conflicts, assuming that the start and end times of maintenance windows in the same power supply section are synchronized, a mixed-integer programming model is constructed, incorporating the constraints of train operation and maintenance window opening comprehensively. The objective of model is to maximize the train working condition overlap time while minimizing the total travel time. Based on the characteristics of the model, the ε-constraint method and GUROBI are used for solution. The effectiveness of the model and algorithm is verified through a case study. The results show that the algorithm can effectively solve the problem, increasing the total overlap time of train working conditions by 24.39% compared to pre-optimization. The research results can provide a reference for the transportation organization decision-making on long and steep gradient lines.

Key words: railway transportation, overlap time of train operation conditions, ε-constraint method, train operation diagram, maintenance skylight, long and steep ramp

中图分类号:

U292.41

田志强, 刘磊, 孙国锋, 张俊峰, 梁辉. 铁路长大坡道线路考虑维修天窗设置的列车运行图优化[J]. 交通运输系统工程与信息, 2025, 25(3): 288-298.

TIAN Zhiqiang, LIU Lei, SUN Guofeng, ZHANG Junfeng, LIANG Hui. Optimization of Train Operation Diagram Considering Maintenance Windows on Railway Lines with Long and Steep Gradients[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(3): 288-298.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/10.16097/j.cnki.1009-6744.2025.03.026

http://www.tseit.org.cn/CN/Y2025/V25/I3/288

参考文献

[1]张天伟,梁巍,佟璐.高速铁路夜行列车运行与天窗设置协同优化线性规划模型[J/OL]. 铁道学报, (2024 06-13) [2024-12-01]. http://kns.cnki.net/kcms/detail/ 11.2104.U.20240612.1530.002.html. [ZHANG T W, LIANG W, TONG L. Linear programming collaborative optimization model on operation of over-night train and setting of maintenance time window[J]. Journal of the China Railway Society, (2024-06-13) [2024-12-01]. http://kns.cnki.net/ kcms/ detail/ 11. 2104. U. 20240612. 1530.002.html.]

[2]穆策,孟令云,廖正文,等.维修天窗与列车运行图一体化编制模型[J]. 铁道科学与工程学报,2018,15(8): 2155-2162. [MU C, MENG L Y, LIAO Z W, et al. Integrated optimization model on maintenance time window and train timetabling[J]. Journal of Railway Science and Engineering, 2018, 15(8): 2155-2162.]

[3]袁博,李海鹰,廖正文.高速铁路动卧开行日列车运行图与维修天窗协调优化[J]. 铁道科学与工程学报, 2024, 21(4): 1309-1319. [YUAN B, LI H Y, LIAO Z W. Integrated optimization on train timetabling and maintenance time for the operation day of high-speed sleeper trains[J]. Journal of Railway Science and Engineering, 2024, 21(4): 1309-1319.]

[4]高如虎,王倩瑜,牛惠民.高铁快运夜间列车服务方案集成优化[J]. 交通运输系统工程与信息,2024,24(6): 254-264. [GAO R H, WANG Q Y, NIU H M. Collaborative optimization for overnight train service plan of high-speed railway express[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(6): 254-264.]

[5]LUAN X, MIAO J, MENG L, et al. Integrated optimization on train scheduling and preventive maintenance time slots planning[J]. Transportation Research Part C: Emerging Technologies, 2017, 80: 329-359.

[6]ZHANG C, GAO Y, YANG L, et al. Joint optimization of train scheduling and maintenance planning in a railway network: A heuristic algorithm using Lagrangian relaxation[J]. Transportation Research Methodological, 2020, 134: 64-92. Part B: [7]YANG H, NI S, HUO H, et al. Integrated robust optimization of maintenance windows and train timetables using ADMM-driven and nested simulation heuristic algorithm[J]. Transportation Research Part C: Emerging Technologies, 2024, 160: 104526.

[8]YANG X, LI X, GAO Z, et al. A cooperative scheduling model for timetable optimization in subway systems[J]. IEEE Transactions on Intelligent Transportation Systems, 2012, 14(1): 438-447.

[9]冯瑜,陈绍宽,冉昕晨,等.考虑再生制动能利用的城市轨道交通列车节能运行优化方法研究[J].铁道学报, 2018, 40(2): 15-22. [FENG Y, CHEN S K, RAN X C, et al. Energy saving operation of urban rail transit trains through the use of regenerative braking energy[J]. Journal of the China Railway Society, 2018, 40(2): 15-22.]

[10] 章鹏. 超长大坡道条件下西成高铁节能优化研究[D].成都: 西南交通大学, 2021. [ZHANG P. Study on energy saving optimization of Xi'an-Chengdu high speed railway under the condition df super long ramp[D]. Chengdu: Southwest Jiaotong University, 2021.]

[11] 柏赟, 周雨鹤,邱宇,等.长大下坡道区间地铁列车节能操纵方法[J]. 中国铁道科学,2018, 39(1): 108-115. [BAI Y, ZHOU Y H, QIU Y, et al. Energy-efficient control method for subway train in section with long heavy down grade[J]. China Railway Science, 2018, 39 (1): 108-115.]

[12] 彭其渊, 李文新,王艺儒,等.基于再生制动的地铁列车开行策略研究[J]. 铁道学报, 2017, 39(3): 7-13. [PENG Q Y, LI W X, WANG Y R, et al. Study on operation strategies for metro trains under regenerative braking[J]. Journal of the China Railway Society, 2017, 39(3): 7-13.]

[13] 赵东升, 赵鹏,姚向明,等.基于工况序列寻优的列车节能操纵策略优化[J]. 交通运输系统工程与信息, 2024, 24(2): 157-165. [ZHAO D S, ZHAO P, YAO X M, et al. An energy-efficient train driving strategy based on regime sequences optimization[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(2): 157-165.]

[14] ZHOU W, HUANG Y, DENG L, et al. Collaborative optimization of energy-efficient train schedule and train circulation plan for urban rail[J]. Energy, 2023, 263: 125599.

[1]	杜剑, 秦可萱, 林姗, 张然, 李洋, 杨忠杰. 考虑集结模式的中欧班列开行方案与运行图联合优化[J]. 交通运输系统工程与信息, 2025, 25(3): 61-72.
[2]	王学楷, 鱼凯, 闫茂德. 动态功率下城轨单向供电不足区域行车调整方法[J]. 交通运输系统工程与信息, 2025, 25(3): 255-265.
[3]	帅斌, 刘一江, 许旻昊, 谢安昊, 孙宗胜, 法慧妍. 高铁快运专列运行图加线方法研究[J]. 交通运输系统工程与信息, 2025, 25(3): 276-287.
[4]	苏焕银, 莫尚霖, 代慧子. 城市轨道交通拟动态随机用户均衡分配方法[J]. 交通运输系统工程与信息, 2025, 25(2): 273-281.
[5]	龚帅宇, 徐行方, 鲁玉. 省域铁路成网条件下列车开行方案优化[J]. 交通运输系统工程与信息, 2025, 25(2): 282-292.
[6]	冯芬玲, 方源, 张泽, 董开云. 风险扰动视角下中欧班列运输网络韧性评估[J]. 交通运输系统工程与信息, 2025, 25(2): 338-351.
[7]	林俊亭, 李茂林, 邱晓辉. 延误场景下列车速度曲线与动态调度联合优化方法[J]. 交通运输系统工程与信息, 2025, 25(1): 173-187.
[8]	吴刚, 杨锋, 江山, 郭茜. 基于霍特林模型的中欧班列最佳补贴值[J]. 交通运输系统工程与信息, 2025, 25(1): 289-297.
[9]	许旻昊, 薛凯肇, 帅斌, 王宇, 杨乔礼, 左静, 张雁鹏. 高速综合检测列车检测区域划分方法研究[J]. 交通运输系统工程与信息, 2025, 25(1): 319-330.
[10]	彭其渊, 江山, 刘思源, 石俊刚, 李登辉, 张永祥. 多干扰下地铁列车运行与车底周转一体化调整优化[J]. 交通运输系统工程与信息, 2024, 24(6): 113-125.
[11]	梁辉, 景云, 孙国锋, 宋琦. 考虑过轨运营模式的市域铁路时刻表优化研究[J]. 交通运输系统工程与信息, 2024, 24(6): 126-134.
[12]	高如虎, 王倩瑜, 牛惠民. 高铁快运夜间列车服务方案集成优化[J]. 交通运输系统工程与信息, 2024, 24(6): 254-264.
[13]	刘兰芬, 杨信丰, 杨珂, 王东梁. 线路运行中断下铁路旅客列车单向接运方案研究[J]. 交通运输系统工程与信息, 2024, 24(6): 265-274.
[14]	李海军, 张晓洋, 高如虎, 魏德华, 陈晓明. 融合麻雀搜索与长短时记忆的疆煤铁路外运量预测[J]. 交通运输系统工程与信息, 2024, 24(5): 14-23.
[15]	曹猛, 袁振洲, 杨洋, 聂英杰, 那艳玲, 孙云超, 陈进杰. 京雄城际铁路全生命周期能耗及碳排放研究[J]. 交通运输系统工程与信息, 2024, 24(5): 37-44.

铁路长大坡道线路考虑维修天窗设置的列车运行图优化

Optimization of Train Operation Diagram Considering Maintenance Windows on Railway Lines with Long and Steep Gradients

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics