Study on Crop Planting Strategies for Rural Areas in North China Based on Multi-Model Optimization

This paper focuses on a rural area in North China, aiming to promote the development of organic crop cultivation and achieve sustainable economic development. Based on the data analysis of organic crop cultivation in 2023, an integer programming model is constructed to deal with the situation of excess production and improve the utilization of land space. A multi-objective planning model is established using the NSGA-II algorithm to predict the seasonal planting schemes for 2024-2030. Then, the Hausdorff distance algorithm is used in combination with the K-means++ clustering method to explore the correlation between crop characteristics and indicators. Finally, Monte Carlo simulation is used to enhance adaptability, and the simulation and solution verification show that the first crop planting should be concentrated on grain crops, while the planting of legumes should be reduced. The second crop planting structure should be inclined towards edible fungi crops, and the crop varieties will be more diversified. These results provide a scientific planting strategy for the rural area, which can effectively promote the rural area to achieve the goal of maximizing economic benefits. It also provides valuable reference for subsequent research and practice.