Bibliothèque de l'Ecole Nationale Supérieure des Travaux Publics - Francis Jeanson "BENSTP-FJ"
Éditeur MIT Press
Documents disponibles chez cet éditeur (1)
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| Titre : |
Ant Colony Optimization |
| Type de document : |
texte imprimé |
| Auteurs : |
Marco Dorigo ; Thomas Stutzle, Auteur |
| Editeur : |
Cambridge : MIT Press |
| Année de publication : |
2004 |
| Importance : |
305 p. |
| Présentation : |
ill., graph. |
| Format : |
24 cm |
| ISBN/ISSN/EAN : |
978-0-262-04219-2 |
| Note générale : |
MIT = Massachusetts Institute of Technology.
Bibliogr. p. [277]-300. Index. |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Optimisation mathématique;Fourmis;Algorithmes optimaux;Mathematical optimization;Ants;Ant algorithms |
| Résumé : |
The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. |
Ant Colony Optimization [texte imprimé] / Marco Dorigo ; Thomas Stutzle, Auteur . - Cambridge : MIT Press, 2004 . - 305 p. : ill., graph. ; 24 cm. ISBN : 978-0-262-04219-2 MIT = Massachusetts Institute of Technology.
Bibliogr. p. [277]-300. Index. Langues : Anglais ( eng)
| Mots-clés : |
Optimisation mathématique;Fourmis;Algorithmes optimaux;Mathematical optimization;Ants;Ant algorithms |
| Résumé : |
The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. |
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