Ant colony optimization(ACO) algorithm is an intelligent algorithm which has a wide range of applications
and better performance, and its search quaility is closely related with the parameters selection. Therefore, aiming at the
large time-consuming problem of the existing improved ACO alogorithm, a novel ACO algorithm based on particle swarm
optimization(PSO) algorithm is proposed. The new pheromone update method is presented, which combines the global
asynchronous feature and elitist strategy. Moreover, the iteration number of ACO algorithm invoked by PSO algorithm
is reduced significantly by large amounts of statistical experiments. The simulation results show that the proposed ACO
algorithm has obvious advantage in search speed when it is used for solving the large-scale traveling salesman problem.