Automatic Pricing and Replenishment Decision-making for Vegetable Commodities Based on TOPSIS Method and ARIMA Model
Junfei Yang, Xinyu Yang, Mingwei Xu · 2023
In recent years, with the growth of China's economy and the significant improvement of people's living and dietary conditions, the demand for fresh produce from consumers has been increasing. However, investigations have found that the replenishment and pricing plans of most supermarket vegetable products are either formulated solely based on past sales experience with low accuracy, or require the establishment of complex neural network models for prediction, which are not suitable for small-scale supermarkets.This article aims at the problem of automatic pricing and replenishment of vegetable commodities. Taking the vegetable categories sold in a supermarket as an example, based on the flow information, wholesale prices and loss rates of vegetable commodities in recent years, the market demand and vegetable categories and orders are analyzed. Based on the regularities of distribution and interrelationships of product sales, on the premise of trying to meet the market demand for various types of vegetable commodities, an optimization model is established with the goal of maximizing the supermarket's revenue to obtain the supermarket's replenishment and pricing strategies, and promote to the formulation of sales strategies for other perishable goods.