Design and Implementation of Grid Material Reserve Strategy Optimization Algorithm Based on Data Mining

In modern logistics management, accurate inventory control is the key to improving overall operational efficiency. This study proposes a “reserve plan configuration” strategy algorithm based on the ABC&PRS classification method for the problem of item classification and inventory strategy configuration in the logistics field. The algorithm comprehensively considers the turnover frequency, demand stability and supply chain risk of items, and realizes the intelligent configuration of reserve strategies for different categories of items by constructing a multi-objective optimization model. The core of the algorithm is to balance inventory costs and service levels, and optimize the allocation of inventory resources through intelligent decision support. The study describes in detail the theoretical basis, design process, implementation method and application verification of the algorithm in simulated logistics scenarios. The experimental results show that the algorithm can effectively improve the adaptability and flexibility of inventory management, and has important practical application value for logistics companies to achieve inventory optimization in the face of complex and changing market environments.