Due to the increasingly severe global energy shortage and the growing awareness of environmental protection, electric vehicles (EVs) have gained attention in the field of fresh food logistics. EVs are favored for their energy efficiency, low carbon emissions, environmental friendliness, and green characteristics. Additionally, the Chinese government's strong support for the new energy industry has further promoted the adoption of EVs in logistics transportation. However, EVs face challenges such as limited driving range, inconvenient charging, and potential issues related to cargo damage and refrigeration for fresh food products. These factors contribute to higher operating costs compared to traditional fuel-powered vehicles. With the improvement of people's living standards in China, there has been an increasing demand for fresh food products and higher expectations for the satisfaction of fresh food cold chain logistics services. Therefore, for purpose of reduce distribution costs of EVs while considering customer satisfaction, this paper focuses on the optimization of routes for electric cold chain logistics vehicles with time windows, taking into account the objective functions of driving costs, time window costs, vehicle utilization costs, customer satisfaction costs during the delivery process, refrigeration costs for fresh food cold chain products, and cargo damage costs during the delivery process. A mathematical model is established, and a modified genetic algorithm is used to analyze the model. Finally, through sensitivity analysis, it is found that increasing the number of delivery vehicles or improving the battery capacity and range of EVs can reduce the total cost of cold chain logistics distribution and improve customer satisfaction.


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    Titel :

    The electric cold chain logistics vehicle routing problem with time windows for battery swap mode considering customer satisfaction


    Beteiligte:
    Shangguan, Wei (Herausgeber:in) / Wu, Jianqing (Herausgeber:in) / Tang, Qitian (Autor:in)

    Kongress:

    Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023) ; 2023 ; Xi'an, China


    Erschienen in:

    Proc. SPIE ; 12989 ; 1298907


    Erscheinungsdatum :

    09.04.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch