The operation of urban rail transit will surely have effect on the original conventional bus system. To realize the development system of “Integration of the two networks, coexistence and common growth” between the rail transit and the conventional bus lines, this article aims to further optimize the layout of the conventional bus lines in connection with the urban rail transit. First of all, this paper analyzes the connection between the original conventional bus stations and the existed rail transit stations, and determines the generating steps of the candidate lines on this basis. Later, this article constructs an optimization model for bus network connected to rail transit, and tries to improve the traditional genetic algorithm by introducing simulated annealing operator. Finally, this article takes Xiguan Cross Station of Lanzhou Rail Transit Line 1 as the example, and applies the improved genetic algorithm to clarify the example, which is meant to verify the effectiveness of the algorithm and to provide the reference for the development of public transportation in Lanzhou City.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Research on the optimal model of public transport route generation for connecting urban rail transit


    Contributors:
    Zhu, Weigen (author) / Hu, weibi (author) / Zhang, Kailun (author)

    Conference:

    International Conference on Algorithms, Microchips and Network Applications ; 2022 ; Zhuhai,China


    Published in:

    Proc. SPIE ; 12176


    Publication date :

    2022-05-06





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Urban rail transit interruption research on passenger route decision making

    Zhao, Ben / Su, Guanghui / Pan, Weiting et al. | British Library Conference Proceedings | 2023


    Urban rail transit interruption research on passenger route decision making

    Zhao, Ben / Su, Guanghui / Pan, Weiting et al. | SPIE | 2023