Research on Agricultural Economic Crop Planting Decision-making Based on Greedy-Simulated Annealing Algorithm

With the global population explosion and accelerated urbanization, food security and sustainable agricultural development are facing serious challenges, especially in China. How to make full use of limited arable land resources to meet the increasingly diversified demand for farm products has become a key issue in agricultural modernization. Under the actual situation of a mountain village in North China, this paper constructs a mixed integer linear programming model to optimize the planting scheme and improve local planting efficiency. The model combines a greedy algorithm with a simulated annealing algorithm, takes crop varieties and economic benefits into account, ensures a reasonable balance between grain crops and economic crops, and determines the planting priority of different crops based on key indicators such as planting cost, mu yield, and market price. The results show that the economic crop planting option is more advantageous under the stagnant sales scenario, with a profit scale of 2.32 million yuan; In contrast, the grain crop planting option is more economically efficient under the sales scenario with falling prices, with an economic crop profit scale of 13.57 million yuan. The study provides theoretical support and optimization references for rural planting planning with limited arable land resources and helps promote agricultural modernization and sustainable rural development.