Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (7): 259-264.DOI: 10.3778/j.issn.1002-8331.1712-0073

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Train Operation Adjustment Based on Artificial Fish Swarm Algorithm

NIU Jincai, LI Maoqing, ZHANG Yanpeng   

  1. School of Automation & Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
  • Online:2019-04-01 Published:2019-04-15

基于人工鱼群算法的列车运行调整方法研究

牛晋财,李茂青,张雁鹏   

  1. 兰州交通大学 自动化与电气工程学院,兰州 730070

Abstract: Due to characteristics of large scale, nonlinearity, strong constraint and difficulty to model, the problem of train operation adjustment is hard to be solved through general operational method. Based on artificial fish swarm algorithm, one adjustment method is firstly proposed and simultaneously the procedures are provided in detail. Specifically, the number of arrival-departure tracks of station and the train overtaking is taken into consideration and then the adjustment model of high-speed railway train is established to minimize the total delay time of train’s entering and leaving the station. Finally, through utilizing the Zhengzhou-Xi’an high-speed rail transport data, the simulation results verify the validity and convergence of proposed method.

Key words: train operation adjustment, fish swarm algorithm, minimum delay time

摘要: 由于列车运行调整是大规模、非线性、强约束、建模困难的问题,用一般运筹学方法不易求解。基于人工鱼群算法,提出列车运行调整方法,并给出了详细的计算步骤。具体的,考虑车站到发线数目约束和列车越行约束,以列车进入车站和驶离车站的总晚点时间最少为目标,建立了高速铁路列车运行调整模型。利用郑西高铁运输数据进行仿真,结果说明人工鱼群算法在列车运行调整中具有有效性和收敛性。

关键词: 列车运行调整, 鱼群算法, 最小晚点时间