This algorithm improves path planning efficiency by enhancing exploration and adaptability in complex environments, showing significant advantages over traditional methods.
Key Points
The SA-HACO algorithm outperformed traditional ACO methods in path length and convergence speed.
Simulation results on both 30x30 and 50x50 grid maps demonstrated enhanced global exploration capabilities.
A unique pheromone diffusion model strengthens the algorithm's ability to avoid local optima.
Differentiated parameters for individual ants improve overall population diversity and adaptability.