Abstract Ant Colony Optimization (ACO) is a new population oriented search metaphor that
has been successfully applied to NP-hard combinatorial optimization problems. In this paper …

Ant Colony Optimization (ACO) is a recent metaheuristic method that is inspired by the
behavior of real ant colonies. In this paper, we review the underlying ideas of this approach …

Ant Colony Optimization (ACO) is a recently proposed metaheuristic inspired by the foraging
behavior of ant colonies. Although it has been experimentally shown to be highly effective …

Recently, a number of algorithms inspired by the foraging behavior of ant colonies have
been applied to the solution of difficult discrete optimization problems. We put these …

Ant Colony Optimization is a relatively new class of meta-heuristic search techniques for
optimization problems. As it is a population-based technique that examines numerous …

ANTS–The International Workshop on Ant Colony Optimization and Swarm Intelligence is
now at its? fth edition. The series started in 1998 with the-ganization of ANTS 1998. At that …

Research on a new metaheuristic for optimization is often initially focused on proof-of-
concept applications. It is only after experimental work has shown the practical interest of the …

Ant Colony Optimization (ACO)[1, 2, 3] is a metaheuristic for solving hard combinatorial
optimization problems inspired by the indirect communication of real ants. In ACO …

Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for
attacking hard combinatorial optimization problems. Yet, its performance, when compared to …

In this paper, we propose a variant of an ACO algorithm called the cunning Ant System (c
AS). In c AS, each ant generates a solution by borrowing a part of a solution which was …