基于群组运行的重载铁路列车运行图优化研究

Optimization of Heavy-haul Train Operating Diagram Based on Group Operation

重载铁路运输主要承担大宗货物运输任务,在保障能源供应和工业生产中发挥着重要作用。随着通信技术的发展,列车群组运行有助于解决既有设施设备导致重载铁路运输能力不足等问题。然而,重载铁路列车群组运行相较于传统模式下的列车运行图,在时间间隔、到发线能力等方面均有差异。通过分析基于群组运行的重载铁路单元列车运输组织特点与开行条件,建立以总旅行时间最小为目标的群组运行的重载铁路单元列车运行图优化模型,设计改进的SPSO粒子群算法进行求解。通过与非群组运行模式下重载铁路列车运行图比较分析,基于群组运行的重载铁路列车运行图中列车的总旅行时间降低2%,总占用时间减少12.5%,实现重载铁路列车高密度编组运行,验证该模型与算法能够显著提高线路的运输能力。

Heavy-haul railway is mainly for the transportation of bulk goods and plays an essential role in ensuring energy supply and industrial production.With the development of communication technology,the operation of train groups can help solve problems such as insufficient heavy-haul railway capacity caused by limitations of existing facilities and equipment.However,the operation of heavy-haul train groups is different from traditional train diagram in terms of interval,arrival and departure line capabilities.This paper first analyzes the characteristics and operating conditions of the transportation organization of heavy-haul unit trains based on group operation.Then an optimization model for the operation diagram of heavy-haul unit trains with minimum total travel time as the objective is established,and an improved SPSO particle swarm algorithm is designed for solution.By comparing and analyzing the operation diagram of heavy-haul trains under non-group operation mode,the total travel time of trains in the group operation based is reduced by 2%,and the total occupancy time is reduced by 12.5%.High-density group operation of heavy-haul trains is realized and this verifies that the model and algorithm can significantly improve the traffic capacity of the line.