Automatic pricing and replenishment decision-making for vegetable products based on optimization models

Abstract

Addressing the replenishment and pricing issues of vegetable products is crucial for ensuring product quality and freshness, optimizing sales combinations, refining pricing strategies, and enhancing operational efficiency. Through scientific data analysis and decision-making, supermarkets can better meet consumer demands, enhance competitiveness, and achieve sustainable development. This paper discusses the complex issues of procurement and pricing of fresh vegetable products in current supermarkets. It employs methods such as hierarchical clustering analysis, Topsis evaluation, and optimization models to construct data models, establishing multiple models to address replenishment and pricing decision-making from various perspectives. The research indicates, firstly, the paper categorizes vegetable products into four clusters, explores complementary and substitute products within them, and discovers that reasonable sales combinations among different types of single products can mutually promote sales, leading to higher economic benefits for supermarkets. Secondly, the paper derives a mathematical model describing the relationship between total profit, total sales volume of individual products, and pricing. This model provides valuable recommendations for supermarkets replenishment and pricing decisions, ensuring practical implementation of pricing and replenishment plans. Thirdly, the paper establishes a model for maximizing profits under constant replenishment quantities, assisting supermarkets in formulating more scientific replenishment plans for individual products within a limited number of available items. By judiciously applying the innovative mathematical models presented in this paper, supermarkets can obtain reliable market analysis and make corresponding replenishment and pricing decisions.