An ant system algorithm with random perturbation behavior for complex traveling salesman problem

Based on the Basic Ant System (BAS) algorithm, a novel Ant System with Random Perturbation Behavior is presented in this paper, and it is applied to solve complex traveling salesman problem. The new algorithm includes two important aspects: a perturbation factor formulated by inverse exponential function is developed, on the other hand, corresponding transition strategy with random selection and perturbation behavior is designed. Numerical simulation demonstrates that the new algorithm possesses more strong global optimization capability, and brings about some good results on reducing CPU time, preventing search from being in stagnation. Furthermore, numeric area and selection method of parameters in the new algorithm are studied.