Research on Multi-stage Inventory Optimization Strategy of Multi-echelon Supply Chain Based on Dynamic Programming Algorithm

Aiming at the multi-stage fluctuation and resource misallocation problems in the process of multi-level supply chain inventory collaboration, this paper constructs an inventory state transfer model and a three-dimensional cost function for the five-level node system, and uses the dynamic programming method to solve the optimal allocation strategy. Based on this, a hierarchical rolling dynamic programming algorithm is designed to achieve the goal of reducing the state space dimension and improving the solution efficiency. Walmart's actual retail order data is made to match the typical demand scenarios, a simulation inspection system is constructed, and several inventory service levels and cost parameters are set. The optimization capabilities of the model in this paper in terms of cost control, response time and inventory turnover are evaluated with the help of systematic indicators. The experimental results show that the proposed method has good stability and robustness when dealing with seasonal and jumpy demands, and has significant engineering application potential. This paper discusses the subsequent research direction of further combining transportation delays and intelligent scheduling strategies.