Research on Vegetable Sales and Inventory Optimization Based on Fuzzy Comprehensive Evaluation

The current sales of fresh vegetables face challenges due to seasonality, perishability, and price fluctuations, necessitating optimized inventory management through precise replenishment and pricing strategies. This study begins with dataset preprocessing to calculate annual sales across individual products and categories, examining correlations between various vegetable categories and personal products. By analyzing average sales volume and revenue per product, this study assess six key factors—unit price, sales volume, wholesale price, loss rate, and daily replenishment—to identify the optimal category choice. Specifically, for July 1st, our analysis recommends prioritizing the purchase of eggplants, moderately purchasing cauliflower, leafy vegetables, chili peppers, and mushrooms, while minimizing root and stem vegetable purchases. Using an evaluation model, this study determined that the average loss rate is the most influential factor, followed by unit price and wholesale price. In contrast, the average profit margin is less critical. This research offers theoretical guidance for automated pricing and replenishment strategies in vegetable sales.