Optimization Model and Algorithm for Fresh Agricultural Products Supply Chain Management based on the Internet of Things and Big Data

The demand for fresh agricultural products is increasing day by day due to the development of the economy and the improvement of people's living standards. Traditional supply chain management methods are difficult to meet the needs of modern agricultural development, the rise of the Internet of Things technology provides new solutions for supply chain management. In order to improve the efficiency of fresh agricultural product supply chain, this paper proposes an optimization model and algorithm for fresh agricultural product supply chain management based on the Internet of Things big data. The model collects data through loT technology and uses big data analysis algorithms to optimize the management of the supply chain. The model algorithm aim to enhance the efficiency and quality of fresh agricultural products supply chain, with a focus on logistics management and demand prediction. This paper first introduces the related technologies of the Internet of Things and big data, and then constructs a supply chain optimization model for fresh agricultural products and designs corresponding algorithms. Ultimately, the analysis confirms the effectiveness and feasibility of the model and algorithm.