Improved Ant Colony Algorithm and Its Application on TSP
Ant colony optimization is one of intelligent optimization algorithms from the observations of ant colonies foraging behavior.However,ACO usually costs more searching time and gets into early stagnation during convergence process.Designs an improved ant colony algorithm.It uses perturbation method and adjusts volatilization coefficient to avoid early stagnation and uses hortation method to improve searching efficiency.Applys the algorithm on traveling salesman problem.It shows that the algorithm can find the best value more quickly,has less average value and gets the best value more stability than MMAS algorithm.