首页> 中文期刊> 《能源与动力工程(英文)》 >Research on Optimization of Freight Train ATO Based on Elite Competition Multi-Objective Particle Swarm Optimization

Research on Optimization of Freight Train ATO Based on Elite Competition Multi-Objective Particle Swarm Optimization

         

摘要

In view of the complex problems that freight train ATO (automatic train operation) needs to comprehensively consider punctuality, energy saving and safety, a dynamics model of the freight train operation process is established based on the safety and the freight train dynamics model in the process of its operation. The algorithm of combining elite competition strategy with multi-objective particle swarm optimization technology is introduced, and the winning particles are obtained through the competition between two elite particles to guide the update of other particles, so as to balance the convergence and distribution of multi-objective particle swarm optimization. The performance comparison experimental results verify the superiority of the proposed algorithm. The simulation experiments of the actual line verify the feasibility of the model and the effectiveness of the proposed algorithm.

著录项

  • 来源
    《能源与动力工程(英文)》 |2021年第4期|P.41-51|共11页
  • 作者单位

    Hunan Province Engineering Research Center for Multi-Energy Collaborative Control Technology College of Automation and Electronics Information Xiangtan University Xiangtan China;

    Hunan Province Engineering Research Center for Multi-Energy Collaborative Control Technology College of Automation and Electronics Information Xiangtan University Xiangtan China;

    The State Key Laboratory of Heavy Duty AC Drive Electric Locomotive Systems Integration Zhuzhou China;

    Hunan Province Engineering Research Center for Multi-Energy Collaborative Control Technology College of Automation and Electronics Information Xiangtan University Xiangtan China;

    Hunan Province Engineering Research Center for Multi-Energy Collaborative Control Technology College of Automation and Electronics Information Xiangtan University Xiangtan China;

    Hunan Province Engineering Research Center for Multi-Energy Collaborative Control Technology College of Automation and Electronics Information Xiangtan University Xiangtan China;

  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类 中国工业经济;
  • 关键词

    Freight Train Automatic Train Operation; Dynamics Model; Competitive Multi-Objective Particle Swarm Optimization Algorithm (CMOPSO); Multi-Objective Optimization;

    机译:货运列车自动列车运行;动力学模型;竞争多目标粒子群优化算法(CMOPSO);多目标优化;
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