文档介绍：Université Libre de Bruxelles
Institut de Recherches Interdisciplinaires
et de Développements en Intelligence Artificielle
An Introduction to
Ant Colony Optimization
Marco Dorigo and Krzysztof Socha
IRIDIA – Technical Report Series
Technical Report No.
TR/IRIDIA/2006-010
April 2006
Last revision: April 2007
Published as a chapter in Approximation Algorithms and Metaheuristics, a book edited by
T. F. Gonzalez.
IRIDIA – Technical Report Series
ISSN 1781-3794
Published by:
IRIDIA, Institut de Recherches Interdisciplinaires
et de D´eveloppements en Intelligence Artificielle
Universite´ Libre de Bruxelles
Av F. D. Roosevelt 50, CP 194/6
1050 Bruxelles, Belgium
Technical report number TR/IRIDIA/2006-010
Revision history:
TR/IRIDIA/2006- April 2006
TR/IRIDIA/2006- February 2007
TR/IRIDIA/2006- April 2007
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An Introduction to Ant Colony Optimization
Marco Dorigo1 and Krzysztof Socha2
IRIDIA, Universit´eLibre de Bruxelles, CP 194/6,
Av. Franklin D. Roosevelt 50, 1050 Brussels, Belgium
April 30, 2007
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IRIDIA – Technical Report Series: TR/IRIDIA/2006-010 1
Introduction
This chapter presents an overview of ant colony optimization (ACO)—a meta-
heuristic inspired by the behavior of real ants. Ant colony optimization was
proposed by Dorigo and colleagues [1–3] as a method for solving bina-
torial optimization problems (COPs).
Ant colony optimization algorithms are part of swarm intelligence, that is,
the research field that studies algorithms insp