基于候车时间和效益损失的城轨列车运行计划优化

doi:10.16097/j.cnki.1009-6744.2023.05.023

交通运输系统工程与信息 ›› 2023, Vol. 23 ›› Issue (5): 215-226.DOI: 10.16097/j.cnki.1009-6744.2023.05.023

• 运输组织优化理论与方法 • 上一篇下一篇

基于候车时间和效益损失的城轨列车运行计划优化

张正坤^1a,1b，朱昌锋^1a,1b，景云^*2，邢进³

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；3. 南京地铁运营有限责任公司，南京 210000

收稿日期:2023-05-14 修回日期:2023-06-18 接受日期:2023-07-10 出版日期:2023-10-25 发布日期:2023-10-23
作者简介:张正坤(1989- )，男，甘肃永登人，讲师，博士
基金资助:
国家自然科学基金(71961016)

Optimization of Urban Rail Train Operation Plan Based on Waiting Time and Benefits Loss

ZHANG Zheng-kun^1a,1b, ZHU Chang-feng^1a,1b, JING Yun^*2, XING Jin³

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; 3. Nanjing Metro Operation Co. Ltd, Nanjing 210000, China

Received:2023-05-14 Revised:2023-06-18 Accepted:2023-07-10 Online:2023-10-25 Published:2023-10-23
Supported by:
National Natural Science Foundation of China (71961016)

摘要/Abstract

摘要： 兼顾乘客和企业的双方利益是编制城轨列车运行计划关注的重点。以两端配有车场的城轨线路为背景，通过考虑列车载客状态及其时间持续对运营效益的影响，提出效益损失概念。针对断面客流不同需求导致效益损失的个体差异，引入体现其差异性的调控因子，以候车时间和效益损失上确界为优化目标，通过考虑列车数量、折返线能力、列车接续及进出场环节等关键约束条件，构建城轨列车运行计划优化模型。因模型求解需要，对模型进行线性化等价重构，并据此设计基于GA(Genetic Algorithm)-Gurobi的混合求解策略。最后，通过算例分析验证了模型及求解策略的合理性，结果分析表明：本文优化得到的列车运行计划节省候车时间约30.1%，减少效益损失约17.9%，节省列车数7.4%，列车运行计划质量得到明显提升。

关键词: 铁路运输, 效益损失, 混合求解策略, 列车运行计划, 城市轨道交通

Abstract: In an urban rail transit line, the conflicting interests of passengers and enterprise are the major focus of the determination of a train operation plan. Given a line with two depots at the terminals, the concept of benefit loss is proposed by considering the operational effectiveness impacted by the passenger loading state of trains as well as its duration. Considering the individual difference of benefit loss caused by various passenger flow demand at each section, a control factor reflecting this difference is introduced in the optimization objective to optimize the waiting time and the supremum of benefit loss. The optimization model considers operational constraints, such as the number of train cars, the turning-back track's capacity, train connection, as well as the process of train entry and exit depots. To facilitate the model solution, the model is linearized, and a GA (Genetic Algorithm)-Gurobi hybrid solution strategy is designed based on the reconstruction principle. Finally, the effectiveness of the model and solution method is verified by an example analysis. The result analysis shows that: the obtained train operation plan can save passenger waiting time by 30.1% , decrease the benefit loss by 17.9% , and reduce train cars by 7.4% . The performance of the train operation plan can be improved by the model and solution method.

Key words: railway transportation, benefit loss, hybrid solution strategy, train operation plan, urban rail transit

中图分类号:

292.4+1

张正坤, 朱昌锋, 景云, 邢进. 基于候车时间和效益损失的城轨列车运行计划优化[J]. 交通运输系统工程与信息, 2023, 23(5): 215-226.

ZHANG Zheng-kun, ZHU Chang-feng, JING Yun, XING Jin. Optimization of Urban Rail Train Operation Plan Based on Waiting Time and Benefits Loss[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(5): 215-226.

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参考文献

[1] SUN L J, JIN J G, LEE D H, et al. Demand-driven timetable design for metro services[J]. Transportation Research Part C, 2014, 46: 284-299.

[2] ZHAO S, YANG H, WU Y H. An integrated approach of train scheduling and rolling stock circulation with skipstopping pattern for urban rail transit lines[J]. Transportation Research Part C, 2021, 128: 103170.

[3] 史峰, 涂纤, 赵烁. 面向O-D时变需求的城轨列车和运行计划优化方法[J]. 中国铁道科学, 2020, 41(1): 115- 125. [SHI F, TU X, ZHAO S. Optimization method of urban rail train operational plan based on O-D time-varying demond[J]. China Rail Way Science, 2020, 41 (1): 115-125.]

[4] WANG Y H, ANDREA D, YIN J T, et al. Passenger demand oriented train scheduling and rolling stock circulation planning for an urban rail transit line[J]. Transportation Research Part B, 2018, 118: 193-227.

[5] YUE Y X, HAN J T. Integrated train timetabling and rolling stock scheduling model based on time-dependent demand for urban rail transit[J]. Computer-aided Civil and Infrastructure Engineering, 2017, 32: 856-873

[6] 张京辉, 陈曦, 李博睿. 考虑车数限制的城市轨道交通非对称时刻表优化[J/OL]. 控制与决策, 2022: 1- 9 [2023-06-10]. https: //doi.org/ 10.13195/ j. kzyjc. 2021. 1807. [ZHANG J H, CHEN X, LI B R. Optimization of asymmetric timetable in urban rail transit considering train quantity restriction[J/OL]. Control and Decision, 2022: 1-9 [2023-06-10]. https: //doi. org/ 10. 13195/ j. kzyjc. 2021.1807.]

[7] 李纵然, 柏赟, 陈垚, 等. 潮汐客流下地铁列车不成对运行图优化模型[J]. 中国铁道科学, 2022, 43(6): 207- 218. [LI Z R, BAI Y, CHEN Y, et al. Optimization model of unpaired timetable for metro trains under asymmetric passenger flow[J]. China Railway Science, 2022, 43(6): 207-218.]

[8] ZHAO Y Q, LI D W, YIN Y H, et al. Integrated optimization of demand-driven timetable, train formation plan and rolling stock circulation with variable running times and dwell times[J]. Transportation Research Part E, 2023, 171: 103035.

[9] 牛惠民. 轨道列车时刻表问题研究综述[J]. 交通运输系统工程与信息, 2021, 21(5): 114-124. [NIU H M. Literature review on rail train timetabling problems[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 114-124.]

[10] 许得杰, 曾俊伟, 麻存瑞, 等. 考虑满载率均衡性的大小交路列车开行方案优化研究[J]. 交通运输系统工程与信息, 2017, 17(6): 185-192. [XU D J, ZENG J W, MA C R, et al. Optimization for train plan of full-length and short-turn routing considering the equilibrium of load factor[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(6): 185-192.]

[11] 史开泉. P-集合, 逆 P-集合与信息智能融合-过滤识别[J]. 计算机科学, 2012, 39(4): 1-13. [SHI K Q. P-sets, inverse P-sets and the intelligent fusion-filter identification of information[J]. Computer Science, 2012, 39(4): 1-13.]

[12] 张正坤. 不同运营模式下城轨列车运行计划优化研究 [D]. 兰州: 兰州交通大学,2022. [ZHANG Z K. Optimization research on urban rail train operation plan under different operating modes[D]. Lanzhou: Lanzhou Jiaotong University, 2022.]

[13] 毛保华, 张政, 陈志杰, 等. 城市轨道交通网络化运营组织技术研究评述[J]. 交通运输系统工程与信息, 2017, 17(6): 115-123. [MAO B H, ZHANG Z, CHEN Z J, et al. A review on operational technologies of urban rail transit networks[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(6): 115-123.]

[14] BERTSIMAS D, SIM M. The price of robustness[J]. Operation Research, 2004, 52(1): 35-53.

[15] 张正坤, 朱昌锋. 改进熵权-TOPSIS法的铁路事故定级模糊评价[J]. 兰州交通大学学报, 2021, 40(1): 31-38. [ZHANG Z K, ZHU C F. Fuzzy evaluation on railway accident classification based on improved entropy weightTOPSIS method[J]. Journal of Lanzhou Jiaotong University, 2021, 40(1): 31-38.]

基于候车时间和效益损失的城轨列车运行计划优化

Optimization of Urban Rail Train Operation Plan Based on Waiting Time and Benefits Loss

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