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VeLP: Vehicle Loading Plan Learning from Human Behavior in Nationwide Logistics System

Summary: VeLP learns vehicle-loading plans from five months of nationwide dispatcher decisions and route data, rather than relying on cargo-volume optimization. Pattern mining and a deep temporal cross network model regular/irregular routes, yielding 35.8–50% gains and 20% planning-time reduction in deployment. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
13656
Venue
VLDB
Year
2024
Pagerank
5.093636e-05
Overall Rank
11,240 | 22.89%
DOI
10.14778/3626292.3626305

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BibTeX Citation

@article{duan_vldb24,
        title = {{VeLP: Vehicle Loading Plan Learning from Human Behavior in Nationwide Logistics System}},
        author = {Duan, Sijing and Lyu, Feng and Zhu, Xin and Ding, Yi and Wang, Haotian and Zhang, Desheng and Liu, Xue and Zhang, Yaoxue and Ren, Ju},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {2},
        pages = {241--249},
        doi = {10.14778/3626292.3626305},
        url = {https://doi.org/10.14778/3626292.3626305},
        year = {2024}
}

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