基于满意度分析的高速铁路列车运行调整优化研究

为了研究高速铁路列车在恶劣天气影响下导致区段临时限速情景下的列车运行调整问题,文中选择总晚点时间和晚点列数2个指标,分别转化为列车延误满意度和正点率满意度,建立线性满意度、梯形满意度和传统多目标线性加权模型,通过改变列车到发时刻、运行径路、次序等实现高效、准点的列车运行调整。最后设计一个限速场景,运用软件求解,通过改变总晚点时间和晚点列数的权重,得到模型的帕累托解,结果表明满意度模型的帕累托解优于线性加权模型。此外,算例验证了梯形满意度线性加权模型从计算时间上优于传统多目标线性加权模型,提出的满意优化模型可以辅助调度员在发布限速命令后尽快获得满意的调度方案。

Research on Train Operation Adjustment of High-Speed Railway Based on Satisfactory Optimization

In order to solve the problem of train operation adjustment for high-speed railway under the scenario of temporary speed limit and the influence of bad weather, two indexes of total delay time and number of delayed trains were selected and transformed into train delay satisfaction and punctuality satisfaction respectively. The linear satisfactory degree model, the trapezoid satisfactory degree model and the traditional multi-objective linear weighting model were constructed through adjusting timetable, operation route, and sequence, to achieve effective and on-time train operation adjustment. A scene of speed limit was designed by software. By changing the weights of total delay time and number of delay trains, pareto solutions were obtained. The result shows the pareto front of satisfactory degree optimization model is better than that of linear weighting optimization model. The example verified the advantage of the trapezoid satisfactory degree optimization model over the traditional multi-objective linear weighting optimization model in terms of computation time. The proposed satisfactory optimization model can assist dispatchers to obtain a satisfactory scheduling scheme as soon as possible after the speed limit command is issued.