Design of agricultural green and low-carbon development path based on multi-objective optimization algorithm

The traditional agricultural development path design fails to effectively deal with the conflicts and trade-offs between multiple objectives, resulting in the lack of flexibility and comprehensiveness of the green and low-carbon agricultural development path in practical application and making it difficult to simultaneously optimize carbon emissions, resource consumption, and economic benefits. To solve this problem, this paper uses a multi-objective optimization algorithm to implement an agricultural green and low-carbon development path design scheme that can balance multiple objectives, aiming to achieve green, low-carbon, and sustainable agricultural development. In terms of methods, this paper first constructs a multi-objective optimization framework based on the non-dominated sorting genetic algorithm II (NSGA-II) to efficiently deal with the conflicts among carbon emissions, resource consumption, and economic benefits. By setting objective weights and objective functions (minimizing carbon emissions, minimizing resource consumption, and maximizing economic benefits) and applying a dynamic weight adjustment mechanism, the path can be optimized in real time according to changes in the external environment. Furthermore, through the life cycle assessment (LCA), the environmental impact of the entire agricultural production process is comprehensively considered. In multiple agricultural production scenarios, the carbon footprint and water footprint of the NSGA-II path are lower than those of the low-carbon and low-resource consumption path optimization (Path 1) and the low-carbon and high-economic benefit path optimization (Path 2). Its eco-efficiency is higher than other paths in most scenarios, with a sustainability index of up to 0.93. Experimental results show that this paper provides an effective agricultural green and low-carbon development scheme.