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Ant Algorithms for Discrete Optimization
Journal article

Ant Algorithms for Discrete Optimization

  • Dorigo, Marco IRIDIA CP 194/6 Université Libre de Bruxelles Avenue Franklin Roosevelt 50 B-1050 Brussels Belgium
  • Caro, Gianni Di IRIDIA CP 194/6 Université Libre de Bruxelles Avenue Franklin Roosevelt 50 B-1050 Brussels Belgium
  • Gambardella, Luca M. IDSIA Corso Elvezia 36 CH-6900 Lugano Switzerland
Published in:
  • Artificial Life. - MIT Press - Journals. - 1999, vol. 5, no. 2, p. 137-172
General Biochemistry, Genetics and Molecular Biology
Artificial Intelligence
English This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterparts as well as the ACO metaheuristic are defined. In the second part of the article a number of applications of ACO algorithms 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 metaheuristic.
Language
  • English
Open access status
closed
Identifiers
Persistent URL
https://sonar.ch/global/documents/280699
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