Due to the shortcomings of max-min ant system(MMAS), which is difficult to decide the lower bound of
pheromone trail and easy to affect by isomorphic problems, a simplified ant colony optimization(SACO) algorithm is
proposed. The upper and lower bound of pheromone trail are limited to a fixed interval and can not be changed with
updating the objective function value. The added pheromone trail is a constant which is independent to the function value.
It is proved that the algorithm not only has the property of linear transformational invariance and translational invariance,
but also its performance is not affected by the lower bound of pheromone trail. Simulation results on the traveling salesman
problem show the feasibility and effectiveness of the presented algorithm.