In modern agricultural production, crop cultivation strategies play a crucial role in sustainable agricultural development. In the context of precision agriculture, this paper tackles the issue of formulating the optimal planting scheme for existing crops. By utilizing historical farming data and crop planting information, etc., a mixed-integer 0-1 programming crop planting strategy model (ROPS) based on the robust optimization method is established. This model aims to maximize the economic returns of all plots while considering constraints such as the area of cultivated land and the degree of discrete planting areas. It also integrates the uncertainties in indicators such as crop yields and expected sales volume. The methodology can incorporate the uncertain information embedded in the indicators into the modelling and produce reasonable model results that allow decision-makers to weigh the risks and benefits to develop optimal solutions. The results indicate that the model was employed to solve the optimal cropping scheme for crops from 2024 to 2030. Through analysis, it was discovered that the average return for the seven years is $8,680,100, which is 35% higher than the initial profit in 2023. The adjusted optimal planting program for crops has significantly improved economic efficiency, and is more beneficial for improving production efficiency and developing organic agriculture, which is of practical significance for promoting the sustainable development of the rural economy.

Shuchang Wang, Jiayi Zeng, Yingshi Wu, Houmin Wang. A mixed integer 0-1 planning crop planting strategy model based on robust optimization. Academic Journal of Computing & Information Science (2025), Vol. 8, Issue 1: 38-47. https://doi.org/10.25236/AJCIS.2025.080106.

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