The basic ACO method was inspired by the behavior of real ant colonies in which a set of artificial ants cooperate in solving a prob- lem by exchanging information via pheromone deposited on a graph. The basic ACO is often to deal with the combinatorial opti- mization problems. The ACO can be used to solve the continuous or discontinuous, nonconvex, nonlinear constrained optimization problems. The characteristics ACO are positive feedback, distrib- uted computation, and the use of constructive greedy heuristic. The ACO method will find an optimal solution if it is run long en- ough, but it should be noted that optimality is traded for efficiency. Their main advantage is that in practice they often find reasonably good solutions in a short time .