高速铁路中间站股道规模配置与列车时刻表的综合优化

高速铁路中间站的股道规模是影响线路通过能力和运输效率的重要因素；由于在高速铁路的规划阶段，很难对线路的远期客流情况进行预估，因此在运营一段时间后，往往需要通过修建侧轨或站台的方式，对线路沿线的中间站的轨道规模进行更新配置。对于高速铁路来说，其线路上运行的列车均为动车组列车，列车的追踪间隔短，发车密度大，在中间站的停站时间不能过长，一般都以快进快出的运营模式进行运营；同时高铁修建和运营具有高成本属性。文中以改建施工成本和总旅行时间作为评价目标，以列车时刻表与中间站股道数量的耦合关系为约束，构建了综合优化模型。在将约束线性化的基础上，借助商业优化软件GAMS和其集成的CPLEX求解器对模型进行了求解。算例结果表明：将中间站的股道规模配置情况和列车时刻表进行综合优化，一方面能够在时刻表中较好地确定列车越行和折返的站点，另一方面能够在最低施工成本的情况下最大限度地满足未来客流的需求。

Comprehensive Optimization of Track Scale Configuration of Intermediate Station and Train Timetable of High-Speed Railway

The track scale of high-speed railway intermediate station is an important factor affecting the line carrying capacity and transportation efficiency. In the planning stage of the high-speed railway line, it is difficult to predict the long-term passenger flow. Therefore, after a period of operation, it is often necessary to update the track scale of intermediate stations along the line by building side tracks or platforms. For high-speed railways, the trains running on their lines are all electric multiple unit trains, with short track intervals, high departure densities and no long dwell time at intermediate stations. Therefore, high-speed railways generally operate in fast-in and fast-out operation mode. At the same time, the construction and operation of high-speed railways have a high cost attribute. The article constructed a comprehensive optimization model with the renovation construction cost and total travel time as the evaluation objectives and the coupling relationship between the train timetable and the number of intermediate station tracks as constraints. On the basis of linearizing the constraints, the model was solved with the help of commercial optimization software GAMS with CPLEX solver. The results of the calculation example show that the comprehensive optimization of the track configuration of the intermediate stations and train timetable can not only determine the stations for train overtaking and turning back in the timetable but also meet the future passenger demand to the greatest extent at the lowest construction cost.