With the improvement of scientific and technological level and the popularization of the 5G network, the distribution mode of "delivery vehicle + drone" has gradually become a new effective distribution method. In order to solve the distribution path optimization problem of the "distribution vehicle + drone" mode of emergency materials under emergencies; In this paper, aiming at the shortest delivery time of "vehicle + drone", by combining theK-Means algorithm, genetic algorithm, and Floyd algorithm, a K-Means optimization genetic algorithm is proposed to solve the model; It is compared and discussed with the individual distribution of vehicles and the joint distribution under the limitation of increased vehicle load; finally, the feasibility of the model and algorithm is verified by numerical example simulation. The experimental results show that the proposed K-Means-based optimal genetic algorithm greatly improves the distribution efficiency of emergency materials in the process and results of the route solution for the "distribution vehicle + drone" distribution mode, compared with the vehicle alone distribution. The path optimization problem provides a scientific basis for decision-making, The actual path that can get the maximum benefit under the balance between the optimal distribution point demand and the maximum load of the vehicle has important research value.


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    Titel :

    Distribution vehicle +drone joint distribution path optimization based on K-means optimization genetic algorithm


    Beteiligte:
    Zhang, Tan (Autor:in) / Jiang, Pengcheng (Autor:in) / Sheng, Kai (Autor:in) / Wang, Xinyan (Autor:in)

    Kongress:

    Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022) ; 2022 ; Guangzhou,China


    Erschienen in:

    Proc. SPIE ; 12591


    Erscheinungsdatum :

    16.02.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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