TITLE:
Research on Optimization of Freight Train ATO Based on Elite Competition Multi-Objective Particle Swarm Optimization
AUTHORS:
Lingzhi Yi, Renzhe Duan, Wang Li, Yihao Wang, Dake Zhang, Bo Liu
KEYWORDS:
Freight Train Automatic Train Operation, Dynamics Model, Competitive Multi-Objective Particle Swarm Optimization Algorithm (CMOPSO), Multi-Objective Optimization
JOURNAL NAME:
Energy and Power Engineering,
Vol.13 No.4B,
April
8,
2021
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.