The price of vegetables in the supermarket is affected by many factors such as the order quantity of the category, the single variety provided by the supplier, the quantity, the loss rate, and the change in customer demand. Most of the factors have a strong correlation with time, and some of them change periodically with time. Models need to be built to solve the relevant decision problems. In this paper, the problem is mainly divided into two parts: 1) to solve the relationship between the total sales of each vegetable category and the cost-plus pricing. 2) figure out the pricing strategy that maximizes profit. In this paper, in order to explore the relationship between the total sales volume and cost-plus pricing, the first two quantitative analyses the functional relationship between the two. Then, in order to construct the constraints of the optimization model, the ARIMA algorithm is used to predict the time series data. In the end, the multi-factor model is simplified into a single-factor optimization model to optimize the pricing strategy of vegetables, and the optimization model is solved based on the differential evolution algorithm.