Enterprise Supply Chain Risk Management and Decision Support Driven by Large Language Models
DOI:
https://doi.org/10.5281/zenodo.12670581Keywords:
ai algorithm, supply chain optimization, demand forecasting, intelligent schedulingAbstract
This paper explores the application and advantages of large-scale AI models in logistics and supply chains. Traditional enterprises need help with the timely detection of anomalies in the supply chain. At the same time, AI algorithms can quickly identify abnormal patterns in the data and issue alerts, helping enterprises adjust real-time strategies to ensure the supply chain's stable operation. AI also reduces inventory costs and economic losses by predicting changes in market demand and optimizing inventory management. In addition, AI models perform well in intelligent scheduling and route planning, providing optimized solutions based on factors such as traffic flow, road conditions, and weather forecasts to improve transportation efficiency and accuracy. The article details the system architecture and functional modules designed to help enterprises meet the transformation challenges of the digital age.
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Copyright (c) 2024 Zeqiu Xu, Lingfeng Guo, Shuwen Zhou, Runze Song, Kaiyi Niu
This work is licensed under a Creative Commons Attribution 4.0 International License.
