Study on Crop Planting Optimization Based on Genetic Algorithm and Monte Carlo Method

Abstract

In the context of limited global land resources, the optimization of crop planting scheme through genetic algorithm and Monte Carlo method can effectively improve the efficiency of agricultural production and resource utilization. Specifically, this study starts from the relevant data of crops in 2023, determines the selling unit price of each crop by using the principle of normal distribution, and after that, takes profit maximization as the objective function, combines the requirements of crop planting, growth pattern, actual conditions and the reality of easy cultivation and management as the constraints and introduces the penalty term to establish the optimization model, and finally uses the Monte Carlo algorithm to determine the original samples and the optimal planting scheme from 2024 to 2030 was studied by genetic algorithm. Finally the seven-year net profit was obtained for different sales programs as 19,869,900 Yuan as well as 30,917,600 Yuan respectively. It shows that selling at half price when stagnant can bring higher benefits to farmers.