杂交粒子群算法在列车运行调整中的应用研究  

Application of crossbreeding particle swarm optimization algorithm in train operation adjustment

作　　者：王瑞峰[1] 孔维珍[1] 詹生正 

机构地区：[1]兰州交通大学自动化与电气工程学院,兰州730070 [2]镇江华东电力设备制造厂,江苏镇江212000

出　　处：《计算机应用研究》2013年第6期1721-1723,共3页Application Research of Computers

摘　　要：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。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.

关 键 词：列车运行调整 城市轨道交通 杂交粒子群算法 仿真 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]