In the subway system, passenger crowding in peak hours is likely to cause train delays that easily propagate to following trains, resulting in a lower efficiency of the system. Consequently, this paper focuses on determining a robust timetable for the trains on the one hand, i.e., finding a better timetable to avoid delay propagation as much as possible in case of a crowded subway system. On the other hand, this paper considers the energy efficiency, i.e., reducing the total energy consumption during operations by selecting appropriate speed profiles and maximizing the utilization of regenerative braking energy. A related mathematical optimization model is formulated with the objective of maximizing the robustness and minimizing the total energy consumption. In order to solve this model, an efficient algorithm, i.e., simulation-based variable neighborhood search algorithm, is presented to obtain a good timetable in reasonable amount of time. Finally, experiments are implemented to show the performance of the proposed algorithm.

在地铁系统中，高峰时段的乘客拥挤很可能会导致火车延误，很容易传播到随后的火车上，从而导致系统效率降低。因此，本文一方面着重于确定列车的可靠时刻表，即在地铁系统拥挤的情况下，找到更好的时刻表，以尽可能避免延迟传播。另一方面，本文考虑了能量效率，即通过选择合适的速度曲线并最大程度地利用再生制动能量来减少运行期间的总能耗。制定了相关的数学优化模型，目的是最大化鲁棒性并最小化总能耗。为了解决这个模型，一种有效的算法，即 提出了一种基于仿真的变量邻域搜索算法，以在合理的时间内获得良好的时间表。最后，通过实验证明了该算法的性能。