In order to solve the problems caused by the traditional ant colony algorithm, such as searching slowly, cling to prematurity, standstill, and the inefficient and useless redundant iteration caused by feedback underutilized in traditional immune algorithm，an algorithm combined ant colony algorithm and Immune Clone hybrid algorithm was proposed. With this algorithm, initial information distribution of ant colony algorithm was generated by immune algorithm in the early work, and the information on the path was adjusted by path concentration of inhibition mechanism at latter work, which kept diversity of ant colony. The algorithm was used to solve the traveling salesman problem for computer simulation.The experimental results showed that the algorithm has targeted improvements, good convergence speed and optimization capabilities.
