Optimization of crop cultivation based on Monte Carlo simulation and linear programming

With the advancement of agricultural modernization, crop planting optimization faces challenges of price fluctuation risk and diversified constraints, necessitating the combination of Monte Carlo simulation with linear planning for scientific decision-making. This study quantifies crop planting rules based on 2023 data including expected sales volume, planting cost, yield, and sales price, establishing a comprehensive planning model. The sales price of each crop is obtained through Monte Carlo simulation method. By ensuring full land utilization and minimizing crop waste to maximize benefits, the model yields a maximum gain of 52.672 billion yuan. When adjusting the objective function to calculate excess production at 50% of the sales price, the maximum gain becomes 23.671 billion yuan. This research provides scientific decision support for agricultural production, optimizes land resource allocation, enhances risk resistance capacity, and promotes agricultural efficiency. By incorporating agronomic requirements such as legume crop planting, the model supports sustainable agricultural development and digital transformation, significantly contributing to agricultural modernization and rural economic development.