This paper considers a last-mile distribution system consisting of a fleet of electric vehicles, where each vehicle has the option to be equipped with a single drone. We formulate the system as a mixed-fleet electric vehicle-drone routing problem, with the objective of minimizing the total cost of the system. Subsequently, an adaptive memetic algorithm with a Q-learning-based operator selection mechanism is employed to solve the model. A set of extensive numerical experiments show that the proposed algorithm performs better than the state-of-the-art approaches. Further, we also demonstrate the importance of economies of scale in drone-aided routing problems.


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    Titel :

    Electric Vehicle-Drone Routing Problem with Optional Drone Availability


    Beteiligte:
    Windras Mara, Setyo Tri (Autor:in) / Sarker, Ruhul (Autor:in) / Essam, Daryl (Autor:in) / Elsayed, Saber (Autor:in)


    Erscheinungsdatum :

    2023-09-24


    Format / Umfang :

    890305 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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