In order to study the path optimization problem of multi-type vehicle mixed distribution, a multi-type vehicle mixed distribution path optimization model is established in this paper and the genetic algorithm is used to solve the model. The mixed distribution of multi-type vehicle and the separate distribution of single type vehicle are simulated by an example. The simulation results show that, compared with the gasoline vehicles distributed separately, the mixed distribution of gasoline vehicles and electric vehicles can reduce the carbon emission by 26% and the total cost by 5.4%. Mixed distribution of gasoline and electric vehicles can reduce the total cost by 10% compared with the electric vehicles distributed separately. The research results of this paper can provide effective reference for logistics enterprises to reduce costs and promote the green development of logistics.


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    Titel :

    Path optimization of multi-type vehicle mixed distribution


    Beteiligte:
    Easa, Said (Herausgeber:in) / Wei, Wei (Herausgeber:in) / Teng, Juan (Autor:in) / Ren, Chuanxiang (Autor:in) / Wang, Xiaoqi (Autor:in) / Fu, Fangfang (Autor:in) / Ding, Fujiang (Autor:in) / Zhou, Guangheng (Autor:in)

    Kongress:

    Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023) ; 2023 ; Hangzhou, China


    Erschienen in:

    Proc. SPIE ; 12790


    Erscheinungsdatum :

    07.09.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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