高铁快运夜间列车服务方案集成优化

doi:10.16097/j.cnki.1009-6744.2024.06.022

交通运输系统工程与信息 ›› 2024, Vol. 24 ›› Issue (6): 254-264.DOI: 10.16097/j.cnki.1009-6744.2024.06.022

高铁快运夜间列车服务方案集成优化

高如虎^*1,2，王倩瑜¹，牛惠民¹

1. 兰州交通大学，交通运输学院，兰州730070；2.甘肃民族师范学院，经济与社会发展系，甘肃甘南747000

收稿日期:2024-07-23 修回日期:2024-10-21 接受日期:2024-10-29 出版日期:2024-12-25 发布日期:2024-12-18
作者简介:高如虎(1989- )，男，甘肃庆阳人，副教授，博士。
基金资助:
国家自然科学基金 (72361020)；甘肃省科技厅计划项目 (22JR5RA379)；甘肃省教育厅高校教师创新基金项目 (2023A-037)。

Collaborative Optimization for Overnight Train Service Plan of High-speed Railway Express

GAORuhu^*1,2,WANG Qianyu¹,NIU Huimin¹

1. School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China; 2. Department of Economic and Social Development, Gansu Normal University for Nationalities, Gannan 747000, Gansu, China

Received:2024-07-23 Revised:2024-10-21 Accepted:2024-10-29 Online:2024-12-25 Published:2024-12-18
Supported by:
/National Natural Science Foundation of China (72361020)；Gansu Provincial Science and Technology Department Project, China (22JR5RA379)；Gansu Provincial Department of Education University Teachers Innovation Fund Project, China (2023A-037)。

摘要/Abstract

摘要： 组织夜间高铁快运列车，核心需要解决快件需求和列车运行线与天窗开设的协调匹配关系。本文以高铁快运时变需求为导向，对包含天窗开设方案、快件配装方案及列车时刻表的快运服务方案集成优化。针对适合开行夜间列车的分段矩形天窗形式，以滞留快件数量最小为优化目标，兼顾快件的运到时效性，并系统性地考虑列车运行、快件配装及天窗开设等相关约束，构建高铁快运服务方案集成优化模型。考虑到所构建的模型属于混合整数非线性规划，通过引入辅助变量线性化处理模型，并采用商业优化软件GAMS的CPLEX求解器求解模型。以宁杭高铁为例进行仿真计算，在参数灵敏度分析的基础上，经过51min计算求得分段矩形天窗模式下的夜间高铁快运列车最优综合服务方案。算例表明，计划运输的4000批快件全部被夜间快运列车服务，得到高铁快件需求与快运列车的最佳匹配方案，并且快件均在次日7:00之前运达目的站，实现高铁快件“次晨达”极速运输服务，同时，所开设的天窗也满足线路综合维修的需求。本文为高铁快运的快件精准调度以及高铁快运列车组织提供了决策依据，为后期铁路部门组织开行高铁快运夜间列车提供一定的参考。

关键词: 铁路运输, 服务方案, CPLEX求解器, 高铁快运, 夜间列车, 集成优化

Abstract: To organize the overnight train of high-speed railway express, the interplay among the high-speed rail express demand, train operation and maintenance window setting should be addressed. Oriented by the demand of high speed rail express, this study collaboratively optimizes the express service plan to determine train timetable, express demand assignment and maintenance window setting. Under the mode of segmented rectangular maintenance window, it aims to minimize stranded express demand while ensuring express delivery timelines. The constraints of train operation, express delivery, and maintenance window setting are comprehensively considered. Then, a mixed integer nonlinear programming model is formulate for the high-speed rail express service plan. In order to reduce the difficulty of solving the model, a set of auxiliary variables are introduced to linearize the nonlinear objective function. The commercial optimization software GAMS with CPLEX solver is used to solve the model. Taking the Nanjing Hangzhou high-speed railway as a case study, a comprehensive overnight express service plan is obtained after 51 minutes of calculation based on parameter sensitivity analysis. The result illustrates that all 4000 planned shipments were served by the overnight express train, obtaining the optimal matching between high-speed rail express demand and trains. All shipments were delivered to their destination before 7:00 AM the following day, achieving the "next-morning arrival" rapid transit service. Additionally, the designated maintenance windows met the comprehensive maintenance requirements of the rail line. This study provides a decision-making basis for the high-speed express dispatching and train organization and provides a certain reference for the railway department to organize the future high-speed express night trains operation.

Key words: railway transportation, service plan, CPLEX solver, high-speed rail express, overnight train, collaborative optimization

中图分类号:

U293

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.

GAORuhu, WANG Qianyu, NIU Huimin. 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.

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高铁快运夜间列车服务方案集成优化

Collaborative Optimization for Overnight Train Service Plan of High-speed Railway Express

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