基于客流影响的城轨交通列车运行调整研究

Train operation adjustment of Urban Transit based on passenger flow influence

列车运行调整是城轨交通调度指挥行车的重要内容,但存在约束条件多、搜索空间大、可行解范围小等问题,往往难以获得满意解。为解决该问题,结合城轨交通列车运行特点,本文建立基于客流量影响的列车运行调整优化模型,采用改进粒子群算法进行求解。通过与遗传算法、粒子群算法对比,验证本文模型及算法的有效性。

Train operation adjustment was an important part of dispatching command of Urban Transit. It was difficult to obtain the satisfactory solution because of many constraints, larger search space and small range of feasible solution. According to the operation characteristics of Urban Transit, this article established train operation adjustment optimization model based on passenger flow influence. The Improved Particle Swarm Algorithm was applied to solve the problem. Comparing with the Genetic Algorithm and Particle Swarm Algorithm, the model and the improved Algorithm were tested and verified to be effective.