Abstract

The running curve optimization of Automatic Train Operation system usually takes into account running time, energy consumption and passenger comfort. In this paper, in order to provide more comprehensive optimization and accurate reference of running curve for Automatic Train Operation system, we adopted the multi-objective optimization strategy of genetic algorithm to optimize from five aspects: speeding (safety), parking accuracy, punctuality, energy consumption and comfort. In order to increase the convergence speed of genetic algorithm to the optimal solutions, we propose a modified genetic algorithm, which the penalty function method is added into the fitness objective function. The modified genetic algorithm optimization program is written by M language in MATLAB, and combined with a graphical user interface tool to design the optimization system. Its validity is verified by comparison between the tests based on three different interstation of Shanghai Metro Line 11. The results show that it is effective and practicability to use the designed system to optimize the running curve of Automatic Train Operation system.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.