Several Railway Safety Supervision Trajectories by the Multiple Objectives PSO Algorithm

• Published in: Chinese Control Conference pp. 1707 - 1713
• Main Authors: Liu, Jun, Shi, Tianyun, Jiang, Xiaoan, Ma, Xiaoning, Zhang, Zhenzuo
• Format: Conference Proceeding
• Language: English
• Published: Technical Committee on Control Theory, Chinese Association of Automation 24.07.2023
• Subjects: Intelligent railway; Java; Linear programming; Mathematical models; Pareto front; Pareto solution; particle swarm optimization; Rail transportation; Railway safety; safety supervision; Search problems; Trajectory
• ISSN: 1934-1768
• DOI: 10.23919/CCC58697.2023.10239787

In order to improve the supervision management efficiency on railway safety, several railway safety supervision trajectories are computed and calculated by the multiple objectives PSO algorithm. Firstly, the objective functions, which are mainly composed of the whole distance and the sum square error on solving safety problem time, are introduced to deeply understand the safety supervision trajectory problem. Secondly, the decision variables in each particle are the sorted order according to the optimized parameters and some main steps on the multiple objectives PSO algorithm are also provided to handle with the corresponding problem. Thirdly, numerical results highlight that the multiple objectives PSO algorithm can provide four optimal trajectories for four safety supervisors and it is key to analyze the Pareto front and the Pareto solutions during the whole evolutionary process.