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Research on Vegetable Pricing and Replenishment Based on Exponential Smoothing Model Prediction

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DOI: 10.23977/tracam.2024.040102 | Downloads: 2 | Views: 219

Author(s)

Zhenyu Zhou 1, Yuang Zhang 1, Jiaxing Zhao 1

Affiliation(s)

1 School of Mathematics and Statistics, Hubei Engineering University, Xiaogan, 432000, China

Corresponding Author

Zhenyu Zhou

ABSTRACT

Vegetables and fresh food are necessities in daily life. Their quality and price not only affect the interests of businesses, but also have a direct impact on people's livelihood issues. However, this type of commodity has its particularity, its appearance and quality will deteriorate over time, resulting in the need to discount sales or even unable to sell. Therefore, it is a very important task for businesses to seek to establish a good and healthy supply and marketing channel. This article has established an exponential smoothing model to predict the sales volume of its vegetable categories and individual items respectively. It then solves the problem through optimization model algorithms, calculating the optimal daily replenishment total and pricing strategy, thus maximizing the supermarket's revenue.

KEYWORDS

Exponential Smoothing Forecasting, Optimization Model, Time Series, Pearson Correlation Analysis

CITE THIS PAPER

Zhenyu Zhou, Yuang Zhang, Jiaxing Zhao, Research on Vegetable Pricing and Replenishment Based on Exponential Smoothing Model Prediction. Transactions on Computational and Applied Mathematics (2024) Vol. 4: 11-18. DOI: http://dx.doi.org/10.23977/tracam.2024.040102.

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