Research on Pricing and Replenishment Strategies of Fresh Food Supermarkets Based on Support Vector Regression and Backpack Problem Modeling

With the improvement of people's living standards, fresh produce superstores are gradually favored by consumers. To better meet the market demand and maximize profits, this paper carries out an in-depth study on the pricing and replenishment strategy of vegetable goods. Firstly, data preprocessing is carried out to ensure its validity and accuracy; secondly, sales patterns are revealed through statistical analysis and clustering methods; furthermore, optimization models and support vector regression are used to predict sales strategies; finally, the optimal combination of commodities is screened out based on the knapsack problem using the greedy algorithm in order to maximize the profitability of the superstore.