杂交粒子群算法在列车运行调整中的应用研究

针对列车运行调整存在约束条件多、求解难度大等问题, 结合城市轨道交通列车运行特点, 建立了优化的列车运行调整模型。在此基础上, 引入遗传算法中的杂交思想, 采用改进后的粒子群算法对此模型进行求解, 给出了求解算法的具体步骤, 并采用西安地铁2号线数据进行仿真验证。结果表明, 采用杂交粒子群算法解决列车运行调整问题是一种有效的方法, 并且其优化能力优于标准粒子群算法。

Application of crossbreeding particle swarm optimizationalgorithm in train operation adjustment

Aiming at the problem of numerous constraints and huge search space on train operation adjustment, concerning the characteristic of urban rail transit, this paper established optimizing mathematical model. For this reason, it gave the introduction of the idea of crossbreeding, using the improved algorithm to solve the model, and specific methods and steps of solving. Basing on the data of Xi'an metro line 2, the preparation of program simulation results show that the crossbreeding particle swarm algorithm is an effective way, and optimization capabilities is better than particle swarm optimization.