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)
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Authors
- 1. Sijing Duan (Central South University)
- 2. Feng Lyu (Central South University)
- 3. Xin Zhu (JD Group)
- 4. Yi Ding (Massachusetts Institute of Technology)
- 5. Haotian Wang (JD Group)
- 6. Desheng Zhang (Rutgers University)
- 7. Xue Liu (McGill University)
- 8. Yaoxue Zhang (Tsinghua University)
- 9. Ju Ren (Tsinghua University)
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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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,945 | A Unified Approach to Route Planning for Shared Mobility | 2018 | VLDB | 7.9331237e-05 |
| 3,570 | Davos: A System for Interactive Data-Driven Decision Making | 2021 | VLDB | 7.3008782e-05 |
| 6,302 | Last-Mile Delivery Made Practical: An Efficient Route Planning Framework with Theoretical Guarantees | 2020 | VLDB | 5.9213518e-05 |
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