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

Electronics Information, Xiangtan, Zhuzhou
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引用次数: 0

Abstract

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.
基于精英竞争多目标粒子群算法的货运列车ATO优化研究
针对货运列车ATO(列车自动运行)需要综合考虑准时性、节能性和安全性的复杂问题,基于货运列车运行过程中的安全性和货运列车动力学模型,建立了货运列车运行过程的动力学模型。介绍了将精英竞争策略与多目标粒子群优化技术相结合的算法,通过两个精英粒子之间的竞争获得获胜粒子,引导其他粒子的更新,从而平衡多目标粒子群优化的收敛性和分布性。性能对比实验结果验证了所提算法的优越性。实际线路的仿真实验验证了模型的可行性和算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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