In this paper, a decision analysis method based on time series analysis and planning model is proposed. By establishing multiple regression equations, this paper analyzes the correlation between sales volume and cost-plus pricing, and uses SARIMA model to model the time distribution characteristics of cost data and predict the future trend of data. Furthermore, this paper constructs a linear programming model to maximize the expected revenue, taking into account the constraints such as loss rate and inventory capacity. Finally, the genetic algorithm is used to solve the planning model to achieve the optimal decision of daily replenishment and pricing. The empirical analysis shows that we apply this method to the purchase strategy of supermarkets, and the results can be effectively applied to practical problems.