Abstract: Ant colony optimization is a new heuristic algorithm which has been proven a successful technique for combinawrial optimization problems, but it still has some shortcomings such as stagnation behavior, needing much time and premature convergence. A new algorithm based on path smoothing and dynamic pheromone updating was proposed for overcoming those shortcomings. By path smoothing, in the curly convergence phase, ants will search towards the path with shorter distance; ants will more constructe pheromone in the later convergence phase. By dynamic pheromone updating, algorithm can avoid being trapped into local optimum. The experimental results show that the algorithm presented in this paper has more effective than classical ant colony algorithm.

Key words: Ant colony optimization, Path smoothing, Dynamic pheromone updating