Ant algorithms for discrete optimization

This article presents an overview of recent work on ant algorithms, that is , algorithms for discrete optimization that took inspiration from the obser vation of ant colonies' foraging behavior, and introduces the ant colony op timization (ACO) metaheuristic. In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterp arts as well as the ACO metaheuristic are defined. In the second part of th e article a number of applications of ACO algorithms to combinatorial optim ization and routing in communications networks are described. We conclude w ith a discussion of related work and of some of the most important aspects of the ACO metaheuristic.