改进移动闭塞方式多列车运行粒子群优化算法  

Improved Particle Swarm Optimization Algorithm for Multi-train Operation under Moving Block Mode

作　　者：翁兆奇 孙晓明[2] WENG Zhao-qi;SUN Xiao-ming(Lanzhou Jiaotong University,School of Automation and Electrical Engineering,Lanzhou 730070,China;Liaoning Agricultural Vocational and Technical College,Yingkou 115009,China)

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]辽宁农业职业技术学院,营口115009

出　　处：《内燃机与配件》2021年第3期4-6,共3页Internal Combustion Engine & Parts

摘　　要：闭塞是多列车运行必须要考虑的重要问题。为了提升移动闭塞方式下的多列车运行的闭塞效果,本文提出了一种改进的粒子群算法(Improved Particle Swarm Optimization Algorithm,IPSO)。采用粒子群算法与遗传进化相结合的方式,以有效提升粒子群算法的全局寻优能力。具体的移动闭塞方式下的多列车运行优化算例的仿真结果表明,本文提出的改进的粒子群优化算法具有较佳的优化效果,适合于解决移动闭塞方式下的多列车运行优化问题。Block is an important problem that must be considered in the operation of multiple trains.To improve the blocking effect of multi-train operation under the moving blocking mode,this work proposes an improved particle swarm optimization algorithm(IPSO).The combination of particle swarm optimization and genetic evolution is introduced to improve the global optimization ability of particle swarm optimization.The simulation results of multi-train operation optimization under the moving block mode show that the IPSO algorithm proposed in this paper has better optimization effect and is suitable for solving the multi-train operation optimization problem under the moving block mode.

关 键 词：移动闭塞 多列车运行 粒子群优化算法 遗传进化 

分 类 号：U284.482[交通运输工程—交通信息工程及控制]