Abstract: Due to the differences of operating environment that cause energy consumption, comfort, punctuality and accurate parking in high-speed trains running process, this paper uses genetic algorithm to optimize the energy saving curve and multi-objective curve, combined with the train traction calculating equation and selected line constraint conditions to get the target curve of ATO traced. The results show that genetic algorithm which optimizes the condition of train conversion makes the proportion of coasting increased, achieving train energy-saving operation. Compared with energy-saving operation, multi-objective one can be better to ensure train operation key indicators in comfort, punctual and accurate park.

Key words: target curve, traction calculation, multi-objective, genetic algorithms

摘要： 对于高速列车在运行过程中因为运行环境造成能耗、舒适、准时和准确停车等指标的不同，运用遗传算法对列车运行的节能性曲线和多目标运行曲线优化，结合列车牵引计算方程和选定的线路约束条件仿真得到列车ATO所要追溯的目标曲线。结果表明：通过遗传算法优化工况转换点使得列车运行中的惰行比例增加，可以实现列车节能运行，与节能性目标相比，多目标可以较好地保证列车运行中的舒适性，准时性和准确停车等关键性指标。

关键词: 目标曲线, 牵引计算, 多目标, 遗传算法