Optimization Model for Crop Planting Scheme Based on Mixed-Integer Programming

In response to the rural revitalization strategy, this paper analyzes and models relevant data based on the crop planting optimization model, aiming to formulate the optimal crop planting scheme for a village in North China. Firstly, data fitting and visualization were carried out, including creating bar charts, frequency distribution histograms, and normal fitting curves of crop yields. Next, the mixed integer programming model was used to optimize and solve the maximum profit and total profit from 2024 to 2030 in the case of overproduction and unsalable surplus. In addition, a sensitivity analysis of data perturbation was conducted for the planting cost to explore the impact of changes in the planting cost on profit, demonstrating that the model has good robustness and stability. This indicates that even when the planting cost is uncertain, the model can maintain stable profit predictions, thus providing effective decision support for crop planting.