Abstract
Most vegetable products have a short shelf life and need to be restocked according to demand after being sold on the same day. Therefore, it is of great significance to accurately price and make effective replenishment decisions for vegetable products under unknown specific unit and purchase prices. This article analyzes the sales information and wholesale prices of various types of vegetables. Using the system clustering method in cluster analysis, the Euclidean distance and shortest distance are obtained based on the characteristic values between different individual products, and the sales volume correlation is classified according to their strength. Then, the chi square test and Fisher exact probability test are used to obtain the sales volume correlation based on the characteristic values between two different categories. The paper constructs a linear programming model with the goal of minimizing daily transportation costs.
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