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Ant colony optimization: models and applications [Guest editorial]
| dc.contributor.author | Cordón García, Oscar |
| dc.contributor.author | Herrera Triguero, Francisco |
| dc.contributor.author | Stützle, Thomas |
| dc.date.accessioned | 2007-10-02T12:36:23Z |
| dc.date.available | 2007-10-02T12:36:23Z |
| dc.date.issued | 2002 |
| dc.identifier.issn | 1134-5632 |
| dc.identifier.uri | http://hdl.handle.net/2099/3630 |
| dc.description.abstract | Ant Colony Optimization (ACO) is a metaheuristic that is inspired by the shortest path searching behavior of various ant species [1,2]. The initial work of Dorigo, Maniezzo and Colorni [3,4] who proposed the first ACO algorithm called Ant System, has stimulated a still strongly increasing number of researchers to develop more sophisticated and better performing ACO algorithms that are used to successfully solve a large number of hard combinatorial optimization problems such as the traveling salesman problem, the quadratic assignment problem, and routing in telecommunication networks. |
| dc.format.extent | 137-139 |
| dc.language.iso | eng |
| dc.publisher | Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica |
| dc.relation.ispartof | Mathware & soft computing . 2002 Vol. 9 Núm. 2 [ -3 ] |
| dc.rights | Reconeixement-NoComercial-CompartirIgual 3.0 Espanya |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
| dc.subject.other | Ant Colony Optimization (ACO) |
| dc.title | Ant colony optimization: models and applications [Guest editorial] |
| dc.type | Review |
| dc.subject.lemac | Intel·ligència artificial |
| dc.subject.lemac | Investigació operativa |
| dc.subject.ams | Classificació AMS::68 Computer science::68T Artificial intelligence |
| dc.rights.access | Open Access |
