Confronted with multiple pressures including population growth and shrinking arable land, optimizing agricultural planting structures through modern management science and mathematical models to rationally allocate limited land resources is crucial for increasing farmers 'income. Based on rural realities, developing organic farming industries by fully utilizing limited arable land resources and adapting to local conditions holds significant practical importance for sustainable rural economic development. To address this, this study proposes a mathematical model combining 0-1 programming and genetic algorithms. This model integrates the compatibility between 0-1 programming and single-crop farming in farmland block division while leveraging genetic algorithms' advantages in multimodal optimization, thereby enhancing farmers' agricultural profits. In the first phase, there is a variation in the values, with the highest reaching ¥9,511,904.00 and the lowest being ¥7,099,057.75. These figures reflect the highest expected profit levels under different circumstances or conditions in the first phase. Moving into the second phase, after taking into account the fluctuations in influencing factors, compared to the first phase, the data in the second phase shows more significant fluctuations. The highest value of ¥9,140,610 is lower than that in the first phase, and the lowest value of ¥5,492,305 is also notably lower than the lowest in the first phase, indicating that the fluctuations in influencing factors in the second phase have had a substantial impact on the profit projections.

Yufei Chen. A Study on Optimal Crop Planting Scheme Based on 0-1 Programming and Genetic Algorithm. Academic Journal of Mathematical Sciences (2026), Vol. 7, Issue 1: 25-29. https://doi.org/10.25236/AJMS.2026.070104.

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