摘要
高铁列车易受到恶劣天气、设备故障、异物入侵等突发事件的影响,导致列车无法按照初始调度计划运行而出现列车晚点。针对高铁列车晚点动态调度问题,引入调整策略控制参数,以列车总晚点时间最小和列车总晚点数量最少之和为目标,建立了高铁列车动态调度非线性规划模型。为提高求解效率,利用动态变化不可行解比例控制参数,提出基于双适值的改进粒子群算法。以南京南到沧州区段实际运行数据为例,将所提粒子群算法与基本粒子群算法、改进遗传算法进行了比较,仿真结果表明了所提算法的优越性。在此基础上深入研究了调整策略控制参数为固定值和动态变化值时的粒子群算法优化效果,仿真结果表明调整策略控制参数值在权重随迭代次数前增后减情况下的求解效果最好。
High-speed trains are susceptible to emergencies such as severe weather,equipment failure,and foreign object invasion,resulting in trains failing to operate according to the initial scheduling plan and appearing late.For the dynamic scheduling problem of high-speed train delay,the adjustment strategy control parameters are introduced,taking the minimum sum of the delayed time and the number of delayed trains as the objective function,and the nonlinear programming model of high-speed train dynamic scheduling is established.In order to improve the efficiency of the solution,an improved particle swarm optimization algorithm based on double fitness is proposed by dynamically changing the infeasible solution proportional control parameters.Taking the actual operation data of Nanjing South to Cangzhou section as an example,the proposed particle swarm optimization algorithm is compared with the basic particle swarm optimization algorithm and the improved genetic algorithm.The simulation results show the superiority of the proposed algorithm.On this basis,the optimization effect of the particle swarm optimization algorithm is deeply studied when the adjustment strategy control parameters are fixed value and dynamic change value.The simulation results show that the solution effect is best when the value of adjustment strategy control parameters increases in the former part and decreases in the latter part with the number of iterations.
作者
林博
俞胜平
刘子源
代学武
崔东亮
韩忻辰
LIN Bo;YU Sheng-ping;LIU Zi-yuan;DAI Xue-wu;CUI Dong-liang;HAN Xin-chen(State Key Laboratory of Synthetical Automation for Process Industries,Northeastern University,Shenyang 110819,China;China Academy of Railway Sciences Co.,Ltd.,Beijing 100081,China)
出处
《控制工程》
CSCD
北大核心
2021年第7期1334-1341,共8页
Control Engineering of China
基金
国家自然科学基金资助项目(U1834211,61790574,61603262,61773269)
辽宁省自然科学基金资助项目(2020-MS-093)
中央高校基本科研业务费(N2008001)。
关键词
突发事件
运行图
动态调度
粒子群算法
Emergency
operation diagram
dynamic scheduling
particle swarm optimization algorithm
