基于客流需求的城市轨道交通动态时刻表优化模型

为使城市轨道交通列车运行时刻表更贴合客流需求,依据不断变化的客流需求确定每列车的发车时刻和停站时间,采用多目标优化方法构建以乘客出行时间费用和列车运行时间费用最小为目标、列车发车时刻和停站时间为决策变量的城市轨道交通动态时刻表优化模型,并采用粒子群算法求解。以广州地铁13号线为例进行验证,结果表明优化后的时刻表更满足客流需求,能有效地提高乘客出行效率,具有更好的动态适应性。

Dynamic timetable optimization model of urban rail transit based on passenger fl ow demand

In order to make the operation schedule of urban rail transit more suitable for the passenger traffic flow demand,the departure time and stop minute of each train are determined based on the changing passenger fl ow demand.The multi-objective optimization method is used to build the dynamic schedule of urban rail transit with the minimum passenger travel time cost and train operation time cost as the goal and the departure time and stop time as the decision variables.The model is optimized and solved by particle swarm optimization.Taking Guangzhou metro line 13 as an example,the results show that the optimized timetable meets the needs of passenger fl ow,effectively improves the effi ciency of passenger travel,and has better dynamic adaptability.