摘要：The basic ant colony algorithm is easy to fall into local optimum and its convergent speed is slow for solving multiple QoS multicast routing problems. Therefore, a crowding ant colony algorithm is proposed in this paper to solve the problems. Crowded degree in artificial fish swarm algorithm is used to adjust nodes transition strategy dynamically according to the congestion of nodes. Stagnation behavior is judged by the similarity of multicast tree and chaos perturbation is utilized to update the pheromone trail on the multicast tree that may fall into local optimum in order that solutions can range out of local optimum. According to simulations, the global search is enhanced at the initial and convergence rate has improved greatly at the later. The improved algorithm is feasible and effective.
关键词：ant colony algorithm;QoS multicast routing;crowding;similarity of multicast tree;chaos
