arXiv：cs.LG（机器学习，全量分类）· Balaji Venkateswaran·· 5 小时前AI 评分21
用机器学习预测供应链管理中的运输时间
Travel Time Prediction in Supply Chain Management Using Machine Learning
AI 导读
一项研究利用机器学习和深度学习，基于大量历史数据构建模型，预测供应链系统中运输与物流的预计运输时间。准确的运输时间估计可帮助供应链成员改善物流一致性与绩效，并支持规划、需求预测、提前期管理和装配计划。该研究共50页，含24张图和8张表。
正文
Abstract:The purpose of this research is to find data and methods using machine learning and deep learning to correctly predict the estimated travel time for transportation and logistics in a supply chain system. The supply chain ecosystem is very complex and heavily relies on the transportation and logistics of raw materials and finished goods. Accurate travel time estimation is critical because it helps supply chain members to improve logistics consistency and performance. This helps in planning, demand forecasting, lead time management and assembly planning. The logistics on the delivery side of the customer also plays a crucial role in customer satisfaction and voice of customer. With the collection of huge historical data and using novel techniques, the research builds an accurate model to predict travel time of inventory.
| Comments: | 50 pages, 24 figures, 8 tables |
| Subjects: | Machine Learning (cs.LG); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2609.38190 [cs.LG] |
| (or arXiv:2609.38190v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2609.38190 arXiv-issued DOI via DataCite |
Submission history
From: Balaji Venkateswaran Dr [view email]
[v1]
Sat, 5 Sep 2026 14:10:23 UTC (6,066 KB)
来源：arXiv：cs.LG（机器学习，全量分类） · arxiv.org