Research On Replenishment Decision of Vegetable Commodities Based on Seasonal Decomposition Exponential Smoothing Method and Objective Programming Model

Abstract

 Vegetables are indispensable in people’s daily lives and represent a high proportion of the goods sold in supermarkets and bring in a large amount of profit. Therefore, the replenishment and pricing decisions on the day of sales are particularly important. In order to make the best replenishment decision, this paper firstly solves the relationship equation between the sales volume of each vegetable category and the cost-plus ratio coefficient based on the least square fitting; secondly, considering the cyclical change of the vegetable sales volume, the seasonal decomposition of the exponential smoothing method is used to predict the demand for each vegetable category in the first week of July; lastly, the profitability optimization function of the superstore is set up: the objective function is the total profit of the superstore, and the decision variables are the daily supply of each vegetable category. The objective function is the total profit of the hypermarket, the decision variables are the daily supply of each vegetable category and the cost-plus ratio coefficient, and the constraints consider the maximum inventory of the hypermarket, the supply is greater than the demand and is less than the maximum value of the historical sales volume. The maximum daily profit and the optimal cost-plus ratio of the hypermarket are finally solved. This study has reference value for vegetable commodity replenishment decision.