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Academic Journal of Computing & Information Science, 2023, 6(13); doi: 10.25236/AJCIS.2023.061315.

Research on Vegetable Pricing Strategy of Supermarket Based on Statistical Analysis and Optimization Algorithm

Author(s)

Xinpeng Yu1, Xiaoqiao Qin2, Yasong Cao3, Ninghui Wu3, Yaqi Tu2, Ziyang Yu2

Corresponding Author:
Ziyang Yu
Affiliation(s)

1School of Electronic Engineering, Guilin Institute of Information Technology, Guilin, China

2School of Information Engineering, Guilin Institute of Information Technology, Guilin, China

3School of Mechanical and Electrical Engineering, Guilin Institute of Information Technology, Guilin, China

Abstract

With the development of social economy, consumers' demand for the quality of vegetables is increasing, and the quality of vegetable goods changes over time. In this paper, we address the issue of the stocking volume and pricing strategy of vegetables in superstores and adopt statistical methods and programming language for data preprocessing, including data searching, cleaning, transforming, integrating and statute, aiming to optimize the pricing of vegetables. First, this study analyzes the relationship between vegetable category and single product sales and time through Pearson coefficient to reveal the sales distribution patterns and interrelationships. Second, a mathematical model is used to predict the restocking volume and pricing strategy of the superstore in the coming week, and the revenue is maximized through model diagnosis, fitting function selection and optimization of the SLSQP algorithm. Finally, the Northern Eagle optimization algorithm is used to screen and optimize the price of saleable individual items in combination with the restocking volume and pricing constraints to improve the profit of the superstore.

Keywords

Vegetable pricing strategy; Data preprocessing; Pearson's coefficient; Mathematical model; Optimization algorithm

Cite This Paper

Xinpeng Yu, Xiaoqiao Qin, Yasong Cao, Ninghui Wu, Yaqi Tu, Ziyang Yu. Research on Vegetable Pricing Strategy of Supermarket Based on Statistical Analysis and Optimization Algorithm. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 13: 99-106. https://doi.org/10.25236/AJCIS.2023.061315.

References

[1] Zhao Yao; Yu Lijuan; Su Yixin; Zheng Tuo; Tong Guangbo. Cleaning and de-duplication of grid load data based on cluster analysis and Pearson correlation coefficient method [J]. Ship Power Technology, 2023, 43(06):69-75. DOI:10.13632/j.meee.2023.06.019

[2] Guo, L.; Guo, Z. X.; Jia, H. T.; Fan, R. Y. Identification of residential electricity theft based on Pearson correlation coefficient and SVM [J]. Journal of Hebei University (Natural Science Edition), 2023, 43(04):357-363.

[3] GUO Zuoxiang; LIU Dongpeng. Evaluation of hand-foot-mouth disease incidence in Zhangye City based on autoregressive moving average model [J]. Chinese Journal of Viral Diseases, 2023, 13(05):390-394. DOI:10.16505/j.2095-0136.2023.5013

[4] Jing Wang; Miaomiao He; Jian Ding; Yonghua Li. A spatio-temporal graph convolutional network for multidimensional time series anomaly detection [J/OL]. Journal of Xi'an University of Electronic Science and Technology, 1-11[2023-11-21] https://doi.org/10.19665/j.issn1001-2400.20230804.

[5] An Yuyuan; Jia Chaowen; Hu Liuchun; Zhang Xueshuai; Liu Xiang; Yan Bo; Li Yanping. A high-resolution and high-precision direction finding method for virtual interferometer based on linear prediction model [J]. Electronic Information Countermeasures Technology, 2021, 36(02):14-17.