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Automatic Pricing and Replenishment Decision Making for Vegetable Products Based on SARIMA and Nonlinear Programming

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DOI: 10.23977/tracam.2024.040103 | Downloads: 2 | Views: 280


Gaofeng Zhu 1, Luyao Xin 2, Wenhuan Yang 2


1 College of Enginerring, Huaqiao University, Quanzhou, 362021, China
2 School of Mathematical Sciences, Huaqiao University, Quanzhou, 362021, China

Corresponding Author

Gaofeng Zhu


In this paper, for the automatic pricing and replenishment decision problem of vegetable goods, firstly, vegetable single items are divided into four categories according to sales volume, and the statistics of the number of vegetable single items with newly classified vegetable single items in each category are counted, and the cosine similarity is calculated, and it is found that: the similarity between the various categories is extremely high, and it is generally higher than 0.8. Then, three vegetable single items of Niushou lettuce, broccoli and net lotus root (1) are randomly selected, and the selected items are subjected to a smooth. Then, three vegetable items were randomly selected, and a smooth time series test was performed on the selected items, and the significance P-values of 0.000, 0.001 and 0.032 were obtained, indicating that the distribution of sales volume of vegetable items showed significant seasonality. Multivariate logistic regression was then used to show that total sales volume is negatively related to cost-plus pricing. With regard to the total daily replenishment and pricing strategy of each vegetable category in the coming week, the objective function is constructed with the orientation of maximizing the supermarket's revenue, and the maximum value of the total daily replenishment in the coming week is predicted by using SARIMA, and then considering the quantity constraints of each category and other conditions, the maximum value of the product's revenue from 1 to 7 July 2023 is solved to be ¥15,214.83, and the corresponding daily replenishment and pricing strategy is obtained. The total daily replenishment and pricing strategy are obtained accordingly.


Pricing and Replenishment of Vegetable Commodities, Cosine Similarity, SARIMA, Multiple Logistic Regression, Nonlinear Programming


Gaofeng Zhu, Luyao Xin, Wenhuan Yang, Automatic Pricing and Replenishment Decision Making for Vegetable Products Based on SARIMA and Nonlinear Programming. Transactions on Computational and Applied Mathematics (2024) Vol. 4: 19-28. DOI:


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