基于速度变异粒子群算法的列车运行策略优化

Train Operation Strategy Optimization Based on Velocity Mutation Particle Swarm Algorithm

为了提高列车在运行过程中的能源利用率,采用速度变异的粒子群算法,对列车运行控制策略进行优化.根据列车运行的机械能理论和能耗理论,建立了以能耗为目标,满足距离、时间和速度约束的列车运行仿真模型,在确定的工况序列条件下,求解列车最优控制策略.改进粒子群算法按照一定的概率,对最小速度进行变异,拓展了粒子有效搜索空间,从而改善优化结果.算例仿真验证了该方法的有效性和合理性.

For the purpose of improving train running efficiency ,a velocity mutation particle swarm optimization （VMPSO） algorithm is applied in optimization of train control strategy .A train operation and movement model is presented based on mechanical theory of train control process and train energy consumption theory .The distance , interval and speed constraints are taken into account in this model .Under certain input control sequences ,this optimization problem is solved by VMPSO algorithm .The minimal velocity is mutated according to some probability in PSO algorithm to exploit the searching scope of optimal solution .Numerical simulation is presented to verify the effectiveness and reasonableness of the method .