Various natural systems teach us that very simple individual organisms can create systems able to solve the complex problems like optimization. Ant Colony Optimization (ACO) is an agent-based technique, which simulates the natural behavior of ants and develops mechanisms of cooperation and learning. Ant Colony Optimization is a metaheuristic approach for solving hard combinatorial optimization problems. The main idea of ACO is to model a problem as the search for a minimum cost path in a graph. Ant Colony Optimization has been successfully applied to scheduling, vehicle routing, and the sequential ordering problems. A review of several Ant Colony Optimization algorithms is done in this paper.