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.
Optimization of highway freight vehicle distribution scheduling based on carpooling mode
International Conference on Smart Transportation and City Engineering (STCE 2024) ; 2024 ; Chongqing, China
Proc. SPIE ; 13575 ; 1357510
28.04.2025
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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