Abstract
In fresh food superstores, the freshness date of general vegetable commodities tends to be relatively short, and the quality of vegetable commodities will deteriorate with the delay of the sales time. Therefore, how to allow supermarkets to ensure that the daily replenishment of the amount of market demand for various types of vegetable products while trying to meet the premise of maximizing their profits has become an urgent problem, this study aims to propose an innovative vegetable product prediction model based on big data, which adopts the SARIMA model to accurately predict the daily replenishment amount of each type of vegetable product in supermarkets. Meanwhile, based on the replenishment amount, the WOA model takes the addition coefficient and sales of different vegetable products as the dependent variable, and the final profit as the independent variable. The corresponding pricing strategy is formulated to maximize the profitability of the supermarket. Through solving the model, it is found that the maximum profit of the supermarket's vegetable products in the next week is 3,649.65 yuan.
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