Automated Pricing and Replenishment Decision Modeling for Supermarket Vegetables

Luoyi Zheng; Zhiyan Lou

doi:10.62051/t6g4w875

Authors

Luoyi Zheng
Zhiyan Lou

DOI:

https://doi.org/10.62051/t6g4w875

Keywords:

SARIMA Model; Spearman Correlation Coefficient; NAR Neural Network; Nonlinear Programming Model.

Abstract

This paper analyzes the historical sales data of vegetable products in a fresh food supermarket, and explores the automatic pricing and replenishment decision-making scheme of vegetable products in this supermarket. Firstly, we integrate and clean the attached data, and then we solve the characteristics and interrelationships of individual products and categories by establishing SARIMA model and Spearman's correlation coefficient model, and then we use nonlinear regression model, nonlinear autoregressive neural network model and optimization model to realize automatic pricing and replenishment decision-making for vegetable products.

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