Adaptive Stochastic Inventory Control Algorithm for Supply Chain Based on Deep Learning Supported By Internet of Things

In a distributed inventory system based on a coordination center composed of several warehouses, the coordination center plays the role of joint inventory management. Each customer sends an order to the coordination center, and the coordination center designates the corresponding warehouse to supply goods according to each customer’s location, delivery date, demand T and the inventory situation of each warehouse. In addition, the supply chain inventory model for a class of perishable goods also has requirements for customer demand satisfaction time, customer demand satisfaction rate and total system cost. In the face of these problems, the coordination of supply chain system can be effectively improved from the perspective of inventory supply, and the average customer demand satisfaction rate can be improved. This paper studies the control strategy and optimization method of multi-level inventory in coordinated supply chain, and mainly summarizes the existing domestic and foreign research from three aspects: supply chain structure, model objective function and solution algorithm, and supply chain inventory control strategy. In supply chain, as the basic and core link, the original management mode of inventory management has limitations, and it is no longer suitable for the new competition mode. Therefore, in the Internet of Things environment. In the corresponding supply chain, the management mode of inventory management, which is the basic and core link, has limitations and does not match the current market competition mode. Therefore, it is necessary to discuss the basic reform of inventory management in the supply chain based on the Internet of Things environment.