The train rescheduling of high-speed railway is a complex combination optimization problem with multi constraints. According to the characteristics of main line highspeed railway train dispatching section, the intelligent rescheduling model is set up. Initializing population by chaos opposition-based learning, dynamic convergence factor, premature recognition mechanism and dynamic weight four strategies are proposed to improve the execution performance of the grey wolf optimization algorithm. And then it is adopted to solve the rescheduling model. Finally, they are verified by three scenarios. The simulation results confirm that the intelligent rescheduling model and improved grey wolf optimization algorithm are practicability and effectiveness.


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    Title :

    Intelligent Rescheduling Research on Train Dispatching Section of Main Line Highspeed Railway Based on Improved GWO Algorithm


    Contributors:
    Xiaozhao, Zhou (author) / Qi, Zhang (author) / Tao, Wang (author)


    Publication date :

    2020-09-01


    Size :

    582032 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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