The ant colony optimization has deficiencies of slow convergence speed and difficult parameters selection. By analyzing the parameters’effect on the algorithm and comparing multiple parameter optimization methods, adopts the hybrid algorithm of particle swarm optimization and ant colony optimization to optimize parameters, and proposes a fast convergent adaptive ant colony optimization. The simulation of the traveling salesman problem shows that the algorithm is feasible and effective.