列车开行动态需求下动车组运用优化研究

Optimization of Multiple Unit Operation under Dynamic Train Operation Demand

为了使动车组运用计划能够快速响应不同需求场景关联的运行图切换要求,首先构建了一个覆盖两日列车车次的动车组接续网络,深度优先遍历网络中的节点,根据动车组初始状态匹配能够执行的路径并建立对应的动车组备选交路集合。以动车组使用数量、总空驶里程和总接续时间之和最小为优化目标,建立了基于动车组备选交路集的0-1整数规划模型,并以某铁路局管辖的部分高速铁路网络日常图与周末图的实际运营数据为背景设计算例,调用Gurobi求解器对模型进行求解。与人工经验调整方法相比,本方法得到的运用方案使得动车组综合运营费用降低了22.9%,动车组使用数量减少了17辆,动车组单元的平均运行里程提高了35.3%。

In order to make the train-set schedule respond quickly to the switching requirements of train diagrams associated with different demand scenarios, a rolling stock succession network covering two days of train trips is constructed first, and the nodes in the network are traversed in depth priority to match the paths that can be executed according to the initial state of the rolling stock and establish the corresponding set of alternative rolling stock crossings. The 0-1 integer programming model based on the set of alternative crossings of trains is established with the optimization objective of minimizing the sum of the number of trains used, the total empty mileage and the total connection time, and the actual operation data of the daily and weekend diagrams of some high-speed railroad networks under the jurisdiction of a railway bureau are used as the background to design the algorithm and call the Gurobi solver to solve the model. Compared with the manual empirical adjustment method, the application scheme obtained by this method results in a 22.9%reduction in the comprehensive operating cost of the rolling stock, a 17-unit reduction in the number of rolling stock used, and a 35.3% increase in the average operating mileage of the rolling stock units.