Research on Crop Planting Strategies in Rural Areas of North China Based on Bi-Level Optimization

Abstract

To address the increasing demand for food and maximize both yield and economic returns in agricultural production, it is crucial to develop scientifically informed planting strategies for farmers. This study constructs a mathematical model based on Bi-Level Optimization theory to determine the optional crop planting combinations and predict future yields under the specific conditions of northern China. To enhance the model’s comprehensiveness, a state transition function was incorporated, enabling a more dynamic representation of planting scenarios. Additionally, the integration of Monte Carlo simulation further equipped the model with the capability to identify optical solutions across diverse conditions. After model calculations, a detailed planting strategy and an expected income table were given. Overall, this research provides valuable insights into the design of planting strategies that simultaneously maximize yield and economic benefits, laying a solid foundation for future studies in sustainable agricultural planning.