城市轨道交通列车运行调整的粒子群算法研究

摘要

A mathematic model of train operation regulation was built based on the characteristics of train operation organization in this article.This model involved many constraints,had strong limitation of real time and delay spread,so the question was difficult to be solved.The Particle Swarm Optimization had advantages of fast calculation speed and strong convergence,so it was suitable for this model.The Particle Swarm Optimization was applied in this article to solve the train operation regulation problem and implement the high effective solution.%依据列车行车组织的特点,对列车运行调整策略进行研究,建立了列车运行调整模型.模型中涉及的约束条件较多,对实时性和延迟传播有着严格的限制,从而使问题的求解成为难题.在模型的求解过程中,粒子群算法有计算速度快、收敛性强的特点,满足模型实时性的要求.因此在列车运行调整中采用了粒子群算法,实现了列车运行调整的高效求解.