In order to solve the problem of urban freight transportation, unmanned aerial vehicle truck joint distribution of goods is applied. A vehicle machine joint path planning and task allocation model is established with the objective function of minimizing the total delivery time. A combination of genetic algorithm and ant colony algorithm is used to fully utilize the global optimization ability of genetic algorithm and the positive feedback mechanism of ant colony algorithm. The optimal solution of genetic algorithm is used as the initial solution of ant colony algorithm to optimize and solve the model. According to standard calculation examples, the results show that the joint delivery of vehicles and machines can reflect time advantages and meet the related needs of fast and accurate delivery in urban areas.


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    Titel :

    Research on joint delivery path planning and task allocation of drones and trucks


    Beteiligte:
    Wu, Jinsong (Herausgeber:in) / Ma'aram, Azanizawati (Herausgeber:in) / Shen, Liu (Autor:in) / Yong, Zeng (Autor:in)

    Kongress:

    Ninth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2024) ; 2024 ; Guilin, China


    Erschienen in:

    Proc. SPIE ; 13251


    Erscheinungsdatum :

    28.08.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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