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12

FGCS
2000

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Ant algorithms

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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.

Marco Dorigo, Gianni Di Caro, Thomas Stützle

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Added	18 Dec 2010
Updated	18 Dec 2010
Type	Journal
Year	2000
Where	FGCS
Authors	Marco Dorigo, Gianni Di Caro, Thomas Stützle

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