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dc.date.accessioned 2012-11-01T11:33:24Z
dc.date.available 2012-11-01T11:33:24Z
dc.date.issued 2001-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23384
dc.description.abstract Early applications of Ant Colony Optimization (ACO) have been mainly concerned with solving ordering problems (e.g., the Traveling Salesperson Problem). More recently, promising results were obtained for solving the Multiple Knapsack Problem by introducing a modification of the standard Ant System algorithm. In this paper we extend our study on the applicability of the ACO approach to subset problems. The computational study involves its applicability for solving the Maximum Independent Set Problem (MISP). The set of instances tested were either randomly generated by specific methods or taken from the so-called DIMACS benchmark graphs. The reported results which are comparable with different state-of-the-art algorithms show the potential of the ACO approach for solving the MISP. en
dc.language en es
dc.subject Hormigas es
dc.subject Optimization es
dc.subject ant colony optimization en
dc.subject Heuristic methods es
dc.subject maximum independent set problem en
dc.subject ARTIFICIAL INTELLIGENCE es
dc.subject combinatorial optimization en
dc.subject metaheuristics en
dc.title An ant system for the maximum independent set problem en
dc.type Objeto de conferencia es
sedici.creator.person Leguizamón, Guillermo es
sedici.creator.person Michalewicz, Zbigniew es
sedici.creator.person Schutz, Martín es
sedici.description.note Eje: Sistemas inteligentes es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2001-10
sedici.relation.event VII Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)