An integrative decision-making model for the Internet of Things-enabled supply chains of fresh agri-product

The application of new information technologies such as the Internet of Things (IoT) has caused a deep impact on production and operations management in various fields. In this paper, a mixed-integer programming model is proposed to generate integrative decision-making in the IoT-enabled fresh agri-products supply chains. The designed model integrates three key stages, that is, planting, storage, and distribution, to help growers make the optimal decisions for maximising revenue. Decisions are made after comprehensive consideration of market factors such as price and demand as well as agricultural characteristics such as crop yield and shelf life. Results of numerical experiments show that significant improvement of benefits can be obtained through the overall decision-making of planting, storage, and distribution. Additionally, it may be most beneficial for growers to keep the warehouse's storage time and storage capacity at a medium level. The IoT-based integrative decision-making method explored in this study can be applied to other fields including manufacturing to achieve more efficient production and operations management.

Automated summary

This paper proposes an integrated decision-making model for the planting, storage, and distribution stages of IoT-enabled fresh agri-products supply chains. The results of numerical experiments show that overall decision-making can significantly improve benefits, and it is most beneficial for growers to maintain moderate warehouse storage time and capacity.