Designing a reasonable driving schedule is a key step in realizing urban transit priority. In this study, a dynamic optimization strategy based on genetic algorithm (GA) is introduced to analyze urban transit schedules under road capacity and transit vehicle limitation. First, a dynamic scheduling model is established by considering the road congestion situation calculated by road capacity from “time-site” dimension. Second, transit vehicle limitations including vehicle maintenance, driver’s leave, and the vehicle renting business are fused in dynamic scheduling model. Finally, a case study is used to testify the effectiveness of the proposed model. In the experiments, an efficient genetic algorithm is proposed to search optimal scheme in dynamic scheduling model. Accordingly, we compare optimization results of the proposed method to several traditional algorithms. Furthermore, the sensibility of parameters value to optimization results is also discussed in the experiment. The calculating results show the effectiveness and feasibility of the GA based optimization method.


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    Titel :

    Dynamic Optimization for Urban Transit Schedule Based on Genetic Algorithm Considering Resource Limitation


    Beteiligte:
    Tang, Jinjun (Autor:in) / Yang, Yifan (Autor:in) / Hu, Jin (Autor:in) / Li, Lexiao (Autor:in) / Wang, Yiwei (Autor:in)

    Kongress:

    18th COTA International Conference of Transportation Professionals ; 2018 ; Beijing, China


    Erschienen in:

    CICTP 2018 ; 565-575


    Erscheinungsdatum :

    02.07.2018




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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