Solving the traveling salesman problem by a chaos ant colony optimization algorithm

By the use of the properties of ergodicity, randomicity, and regularity of chaos, a chaos ant colony optimization algorithm is proposed to solve the traveling salesman problem. The basic principle of the algorithm is that chaos initialization is adopted to improve individual quality and chaos perturbation is utilized to avoid the search being trapped in local minima. Compared with the standard GA and simulated annealing algorithm, simulation results show that chaos ant colony optimization is a simple and effective algorithm.