Research on Cultivation Optimization Model in Northern China Based on Genetic Algorithm

North China has various terrains and complex farming conditions, including flat and dry land, terraced land, hillside land, watered land and other arable land types, which can be planted with annual or biannual crops. In this paper, based on the cultivation situation in a typical mountainous area in North China in 2023, taking into account the economic benefits, crop characteristics, management convenience and other factors, we use genetic algorithms and robust optimisation to initially establish a cultivation decision model to derive the optimal planting strategy of crops for the next seven years, and then further explore the substitutability between crops, as well as the correlation between the expected sales volume and the sales price by using the MAE and Spearman's correlation coefficient, The model is optimised by exploring the correlation between expected sales volume and sales price, and planting cost through MAE and Spearman correlation coefficient. The model is conducive to improving the utilisation efficiency of arable land, flexibly adjusting the planting strategy according to the market demand, and increasing economic income.