基于改进的粒子群算法的地铁时刻表调整方法研究及实现

为应对突发状况下地铁列车的晚点问题,尽快消除与既定时刻表的偏移时间,采用Visual Studio 2012和SQL Server 12.0数据库搭建时刻表系统,同时建立列车运行动态调整模型,选择改进的粒子群优化算法对模型进行求解,得出消除偏离时间的最优解,完成列车的动态调整仿真。仿真结果表明,该方法通过自动调整多辆列车的站间运行时间和停站时间,能有效地消除晚点时间,恢复列车正常运行。

Metro timetable adjustment based on improved particle swarm optimization

To deal with the problem of metro train delay under the emergency situations, and eliminate the offset time from the established timetable as soon as possible, this article used Visual Studio 2012 and SQL Server 12.0 database to build the timetable system, and establish the automatic adjustment model as well. Besides, the article chose the improved particle swarm optimization and got the optimal solution of the model to implement the simulation of the train dynamic adjustment. The simulation results showed that this method could effectively eliminate the offset time by auto-adjusting multiple trains running times and station dwell times, restore the normal operation of the train.