Artificial ant colony algorithm is new in the evolution computing. The primary study shows it is a better algorithm with robust based population, but it has some shortcomings such as its slow computing speed, and it is easy to fall in local peak in large scale problem. To overcome these deficiencies, an improved ant colony algorithm is designed through abstracting the advantages of particle swarm optimization (PSO).