An Improved Grey Wolf Optimization Algorithm for Planting Structure Optimization in North China Mountainous Area

This study addresses the agricultural planting strategy optimization problem in North China's mountainous area by constructing three progressively in-depth mathematical models. These models consider factors such as planting restrictions, sales, and cost assumptions. An Improved Grey Wolf Optimization algorithm (IGWO) is proposed to solve the established mathematical models. Compared with the standard GWO algorithm, the particle swarm optimization (PSO) algorithm, and the differential evolution (DE) algorithm, the IGWO algorithm increases the economic benefits of agricultural planting structure by approximately 15%. Additionally, the ecological protection index is improved by 10%, and the social development index is increased by 8 %. This research provides a novel approach and perspective for optimizing agricultural planting structures.