The Frontiers of Society, Science and Technology, 2024, 6(4); doi: 10.25236/FSST.2024.060414.
Yanzhi Hua1, Xuan Yang2, Suo Liang1
1School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin, 541004, China
2School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
Vegetables have a short freshness period and are easy to deteriorate, and fresh food supermarkets need to develop reasonable replenishment and pricing strategies in order to improve profitability. In order to analyze the time distribution pattern and interrelationship of various types of vegetable sales and give the optimal replenishment and pricing strategy, this paper firstly analyzes the correlation between various types of vegetable sales by using the spearman correlation coefficient, and the results show that the correlation between sales of leafy and eggplant vegetables is weak only. Then using the elbow rule to determine the vegetable single product sales can be divided into four categories, and k-mean clustering to analyze the time series relationship between the total sales of each cluster. Finally, this paper establishes ARIMA to predict the total daily replenishment of each type of vegetables in the coming week based on the time-order relationship and establishes Nonlinear optimization model based on the prediction results, taking the profit maximization of the superstore as the goal, introduces the demand elasticity improvement model, and ultimately gives the optimal daily replenishment of each vegetable category in the coming week and the pricing strategy, and solves for the maximum total profit of ￥10335.23 .
Elbow Rule, K-means Clustering, Arima, Demand Elasticity, Nonlinear Optimization
Yanzhi Hua, Xuan Yang, Suo Liang. Automatic Pricing and Replenishment Decision of Vegetable Commodities Based on ARIMA—Nonlinear Modeling. The Frontiers of Society, Science and Technology (2024), Vol. 6, Issue 4: 91-96. https://doi.org/10.25236/FSST.2024.060414.
[1] Yang Haoxu. Correlation Analysis of Vegetable Price and Sales—Taking Oil Wheat Vegetable as an Example [J]. Food Safety Guide, 2018, No. 212(21): 179-181.
[2] Xu Guangming, Liu Yihan, Wu Runfa, et al. Optimization method of train stop scheme based on elastic demand [J]. China Railway Science, 2023, 44(06): 184-195.
[3] Gao Mingyu, Cai Linhui, Sun Changcheng. A short-circuit fault detection algorithm for battery pack based on Spearman rank correlation and neural network [J]. Journal of Electronics and Information, 2022, 44(11): 3734-3747.
[4] Wang Chaowei. Study on Typical Day Selection Based on Improved K-means Clustering [D]. Shanghai: shanghai dianji university, 2022(03).
[5] Wu Hui, Wang Jiapeng, Wu Wenjing et al. Prediction and analysis of global gas meter temperature based on ARIMA model [J]. Modern Information Technology, 2023, 7 (16): 147-150.