JAMC
The Sales Combination Strategy of Fresh Supermarket Vegetables Based on Apriori
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Abstract
With the development of the times, the key issue faced by fresh food supermarkets is the challenge of preserving vegetable products and their vulnerability to time, resulting in inventory backlog and increased loss rates. Consumers place greater emphasis on freshness and traceability in the vegetables sold by fresh supermarkets. Studying the sales strategy of vegetables that need to be sold out on the same day in fresh supermarkets has high research value. This article is based on the background of question C in the National College Student Mathematical Modeling Competition of the 2023 Higher Education Society Cup. Python software is used to scan 878504 cumulative data from the supermarket over the past three years. Frequent itemsets are selected and combined with daily vegetable sales. Apriori algorithm is used to determine the daily sales combination. This article obtained a sales mix centered on 11 vegetable items, including Yunnan oilseed rape, brassica campestris, and Sichuan pepper.
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How to cite this paper
The Sales Combination Strategy of Fresh Supermarket Vegetables Based on Apriori
How to cite this paper: Tingting Chen, Zefeng Sun, Hongyu Huang, Sisi Zheng. (2024) The Sales Combination Strategy of Fresh Supermarket Vegetables Based on Apriori. Journal of Applied Mathematics and Computation, 8(1), 88-92.
DOI: http://dx.doi.org/10.26855/jamc.2024.03.011
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