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Based on cultural algorithm, an improved Ant Colony Optimization algorithm(ACO) for Traveling Salesman Problem(TSP) has been proposed. In the improved algorithm, the population space and the belief space of cultural algorithm are redesigned. This algorithm uses double evolutionary mechanisms and the Max-Min Ant System(MMAS) to build the population space, and adopts 3-OPT cross operation for the current optimal solution in the beliefs pace. As the result of this double evolutionary mechanisms, the population space gets higher efficiency of evolution. The simulation results show that the improved algorithm is more effective than Ant Colony Optimization algorithm(ACO) and Cultural Ant Colony Algorithm(CACS), which has faster convergence speed and greater accuracy.