A new pheromone updating strategy in ant colony optimization

This work presents a new pheromone updating strategy , which is used to optimize ACO (ant colony optimization) in solving the traveling salesman problem. At first, the paper introduces the principle, the characteristics, the construction and the realization method about the ACO. Then, an improved ant colony optimization algorithm using a new pheromone updating strategy is proposed. The pheromone trail of each edge is set with a lower limit at the beginning iterations of the algorithm, and the worst ant judged by its tour length like the best ant used in ACO is allowed to perform global trail updating. At last, we demonstrate the efficiency of the algorithm by means of experimental study.