Automatic Pricing and Replenishment Decision Model for Vegetable Products Based on Optimization Algorithm
DOI:
https://doi.org/10.54097/jceim.v11i2.12407Keywords:
Benefit Maximization, Pearson Coefficient Analysis, Linear Programming ModelsAbstract
Due to the short shelf life of vegetable commodities, vegetable superstores need to make replenishment and pricing decisions on a daily basis based on the historical sales and demand of each commodity. Therefore, this paper establishes an optimization model to help superstores filter and analyze data and optimize replenishment and pricing decisions. First of all, we obtained the sales volume distribution data and images of each category over time, analyzed the interrelationship of each vegetable category, studied the "cost-plus pricing" method on this basis, and analyzed the correlation between the total sales volume and cost-plus pricing. Finally, the objective function of maximizing the revenue of the superstore is chosen, and a linear programming model is established under the constraints to obtain the total daily replenishment quantity and pricing strategy of each vegetable category in the coming week, which can maximize the revenue of the superstore.
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