Ant Colony Optimization (ACO) is the best example of how studies intended at understanding and modeling the behavior of ants and other social insects can inspire the development of computational algorithms for the solution of tough mathematical problems. Introduced by Marco Dorigo in his PhD thesis (1992) and initially applied to the travelling salesman problem, the ACO field has experienced an enormous growth, reaching a position of an essential nature-inspired stochastic metaheuristic for optimization of critical problems. This book offers state-of-the-art ACO methods and covers various techniques, comprising of parallel implementations and applications, where current investments of ACO to varied areas, like traffic clog and discipline, structural optimization, manufacturing, and genomics have been demonstrated.