At present, the urban logistics distribution of electric vehicles in the sharing economy has a good development opportunity. Under the premise of vehicle sharing, the bi-level programming method is used to study the location-routing problem of different vehicles in multi-depot considering dynamic energy consumption and profit distribution. This paper considers the influence of the weight of the cargo, the driving distance and the dynamic road network information on the energy consumption of electric vehicles. In order to balance the interests of companies and vehicle owners, a location routing model for electric vehicle distribution is constructed with the objective of minimizing the cost of dispatching vehicles by the company and the minimum energy consumption of the vehicle owners during the whole journey including the return trip, constrained by the hard time window, the maximum vehicle load and the maximum return no-load distance. Design a heuristic algorithm that combines two-layer variable neighborhood search and genetic algorithm to solve the model. The results of case analysis show that the model can obtain satisfactory solutions for companies and vehicle owners. The distribution activities of shared vehicles among multiple distribution centers reduce the total cost of the company, and the vehicle owner completes the distribution task with minimal energy consumption. This paper provides an effective method for solving the location-routing problem of electric logistics distribution network and profit distribution between transportation companies and vehicle owners under the sharing economy.


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    Titel :

    Optimization of electric vehicle distribution path considering profit distribution under the sharing economy


    Beteiligte:
    Kong, Xiangjie (Herausgeber:in) / Falcone, Francisco (Herausgeber:in) / Wang, Haipeng (Autor:in) / Feng, Xiwen (Autor:in)

    Kongress:

    3rd International Conference on Internet of Things and Smart City (IoTSC 2023) ; 2023 ; Chongqing, China


    Erschienen in:

    Proc. SPIE ; 12708


    Erscheinungsdatum :

    14.06.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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