This study presents an optimization approach for large-scale highway freight vehicle distribution through vehicle sharing, leveraging spatio-temporal characteristics of freight demand similarity. We apply Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) to identify shareable clusters, using vehicle delay time and detour distance as key parameters. A highway freight scheduling model is constructed, and an Adaptive Large Neighborhood Search (ALNS) algorithm is employed to generate scheduling plans within the clusters. Results indicate a 30% reduction in vehicle usage, suggesting that freight carpooling can significantly lower transportation costs and enhance the resource allocation efficiency of highway freight systems.


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    Titel :

    Optimization of highway freight vehicle distribution scheduling based on carpooling mode


    Beteiligte:
    Feng, Zhengang (Herausgeber:in) / Mikusova, Miroslava (Herausgeber:in) / Sun, Ziwei (Autor:in) / Sun, Xiuzhen (Autor:in) / Fu, Xin (Autor:in)

    Kongress:

    International Conference on Smart Transportation and City Engineering (STCE 2024) ; 2024 ; Chongqing, China


    Erschienen in:

    Proc. SPIE ; 13575 ; 1357510


    Erscheinungsdatum :

    28.04.2025





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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