Research On Rational Organic Farming Practices Based on A Multifactor Optimization Model Using Genetic Algorithm

Given the global population growth and the shrinking availability of arable land, it is crucial to adapt organic farming techniques to the specific characteristics of rural areas. This approach aims to maximize the utilization of available land and promote the economic development of rural communities. This paper introduces a multifactor optimization strategy to identify the most profitable agricultural farming practices. The model considers various factors, including seasonality, economic conditions, land suitability for planting, climate conditions, market prices, and planting costs. Additionally, it takes both the substitutability and complementarity of crop options into account. By employing a genetic algorithm (GA), the model is designed to identify the highest productivity planting schemes, addressing the complexity and multi-objective nature of agricultural planning. The results demonstrate that the proposed optimization strategy can significantly improve the sustainability and profitability of organic farming practices, enhancing the economic returns for farmers and contributing to the development of rural communities.