A study on commodity pricing and sales optimization based on linear programming model: a case of vegetable category

Yutong Chen

doi:10.54097/ndkega92

Authors

Yutong Chen

DOI:

https://doi.org/10.54097/ndkega92

Keywords:

Linear Programming Models, Merchandise Pricing and Sales Optimization, Vegetable Category.

Abstract

In the fresh food retail industry, vegetable commodities require daily replenishment decisions based on historical sales and demand due to their short freshness period and susceptibility to quality. In this paper, the sales volume, wholesale price and unit price of each category are first extracted, and the cost-plus ratio and related data are calculated. The relationship between the sales volume of each category and the cost markup rate is analyzed through linear regression, and it is concluded that the sales volume of most categories decreases with the increase of the markup rate, and through the distribution of the scatter plot of the total sales volume of the vegetable category and the markup rate, it can be seen that there is a negative correlation between the total sales volume of the vegetable category and the cost markup pricing, and then through the establishment of the optimization model and the prediction of the sales volume of each category for the coming week, the wholesale price and the related data, and the profits are used to Pricing to ensure revenue at the maximum markup rate to develop the total daily capture and pricing strategy for the coming week.

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