Research on grassland grazing environment planning based on GA-ACO hybrid algorithm

Aiming at the problems of overgrazing by pastoralists and the reduction of grassland utilization rate, a Genetic Algorithm-Ant Colony Optimization (GA-ACO) hybrid algorithm was proposed to solve the problem of grazing in pastoral areas. Firstly, the pastoral environment is analyzed, and the overgrazing area and the usable area of the pastoral area are obtained by calculation, and the three types of operators in the genetic algorithm are designed according to the stock carrying capacity, the number of sheep and the grazing days as the standard for dividing the grazing area. Connectivity concept, so as to ensure that the algorithm reasonably divides the pastoral rotation area. Then, on this basis, the information backtracking mechanism and dynamic detection mechanism of the ant colony algorithm are improved, so as to improve the convergence speed of the algorithm and quickly find the shortest path for grazing in grassland pastoral areas. Finally, in order to verify the effectiveness of the hybrid algorithm, random generation maps of different sizes of pastoral areas are used for algorithm simulation experiments. The experimental results show that the algorithm can reasonably divide the rotation grazing area, effectively avoid the overgrazing area, and quickly plan the shortest grazing path, which is the scientific basis for the unmanned aerial vehicle.