Research on Agricultural Planting Strategy Combining Simulated Annealing Algorithm and Linear Programming

This paper investigates an agricultural planting strategy that integrates simulated annealing algorithm and linear programming. Addressing the crop planting issues in mountainous regions of Northern China, an optimization model is proposed, aiming to optimize the cropping structure and enhance production efficiency and economic returns by comprehensively considering factors such as land types, crop adaptability, planting costs, and profits. Data on mountainous land and crops were collected, and the simulated annealing algorithm was employed to refine the initial solution obtained from linear programming, thereby addressing uncertainties and risks in actual production. The model predicts planting yields from 2024 to 2030, revealing a stable growth trend in net income, necessitating close monitoring of market dynamics to mitigate potential risks.