Marco Dorigo and Gianni Di Caro
IRIDIA, Universit´e Libre de Bruxelles
Brussels, Belgium
{mdorigo,gdicaro}@ulb.ac.be
Luca M. Gambardella
IDSIA, Lugano, Switzerland
luca@idsia.ch
Abstract
This paper overviews recent work on ant algorithms, that is, algorithms for discrete
optimization which took inspiration from the observation of ant colonies foraging
behavior, and introduces the ant colony optimization (ACO) meta-heuristic. In the
first part of the paper the basic biological findings on real ants are overviewed, and
their artificial counterparts as well as the ACO meta-heuristic are defined. In the
second part of the paper a number of applications to combinatorial optimization and
routing in communications networks are described. We conclude with a discussion of
related work and of some of the most important aspects of the ACO meta-heuristic
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