Research on the Program to Improve the Economic Efficiency of Crop Cultivation Based on Stochastic Dynamic Programming Model and Genetic Algorithm

Agriculture is the foundation of a country's national economic development, and the progress of agricultural science and technology is the core driving force for the modernization of agriculture. The development and application of automated agricultural machinery and scientific planning technology are beneficial to the improvement of agricultural economic efficiency. In order to reduce the economic risk of crop cultivation caused by seasonal changes, climate fluctuations and plant growth patterns and other uncertainties, and to reasonably allocate various crops to different arable land, combining the advantages of deterministic dynamic planning and stochastic planning, this study constructs a stochastic dynamic planning model and utilizes genetic algorithms, so as to give full play to the optimal efficiency of the crop cultivation economy. By adding constraints to the algorithmic framework, the model of maximizing the total expected return is continuously optimized, which will provide scientific and efficient planting basis for agricultural planting decision-making and has strong practical application value.