Research on the Solution Method of Mixed Integer Nonlinear Planning Model Based on Influence Factor

This paper focuses on the optimization problem of layout decision making under the background of multiple factors, and constructs and solves a mixed integer nonlinear programming model. The research uses a publicly available dataset and defines many symbols to represent key variables. In the construction of the static model, the regression imputation method is used to handle missing data, and future expected values are determined based on the crop data in 2023. By setting decision variables, a model aiming at maximizing profit is constructed, taking into account the area limitations of various types of cultivated land, the minimum planting area of crops, rotation and continuous cropping restrictions and other constraint conditions. For the surplus part, the situations of full price and half price sales are discussed respectively. The dynamic model considers the change rates of various crop data and calculates dynamic adjustment factors to optimize planting decisions. Matlab is used to transform the model into a mixed integer linear programming model for solution, and finally the optimal planting plans under different conditions are obtained, and the influence of various factors on revenue is analyzed, providing a scientific basis for relevant layout decisions.