Vegetables play a vital role in people's daily life; however, due to the short freshness of vegetables, many vegetables that cannot be sold in a short period of time become spoiled and cannot be sold. Based on this kind of problem, the distribution law and correlation of each category of vegetables and its single product are analyzed, and the correlation size between vegetables and their optimal decisions are obtained by using Origin and other software, with the help of the time series model and the objective planning problem. Such models are characterized by stability and reliability. In this paper, in order to determine the sales distribution pattern of vegetables in supermarkets and the correlation between vegetables; firstly, the data are cleaned, and then the data are processed using the principle of classification and aggregation, and then the correlation between vegetables is calculated through the Pearson's correlation coefficient and the heat map is drawn to show it. Through visualization, it is concluded that the six categories of vegetables have an upward trend in sales, and the standing volume of aquatic root vegetables is higher than that of other vegetables, and the sales of chili peppers are cyclical (part of the results), and it is obtained by judging the heat map that except for the strong correlation between edible mushrooms and cauliflower, there is not a strong correlation between the other vegetables. By exploring the sales value and cost-plus pricing of vegetables in the superstore, the replenishment decision and pricing decision are formulated; based on this kind of problem, a time series model is used to predict the sales volume and pricing for the next seven days and the model prediction is tested to obtain a good model fit value, and then combined with the impact of cost-plus pricing and the cost of the factors to formulate the optimal pricing and replenishment decision of the superstore: aquatic rhizome replenishment of the 7-day Strategy: 38.77kg, 38.74kg, etc.

Xinyu Liu, Shuang Li. A study on vegetable pricing replenishment strategy based on seasonal time series. The Frontiers of Society, Science and Technology (2024), Vol. 6, Issue 4: 97-104. https://doi.org/10.25236/FSST.2024.060415.

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