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dc.date.accessioned 2012-09-28T15:46:42Z
dc.date.available 2012-09-28T15:46:42Z
dc.date.issued 2008
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/21765
dc.description.abstract Metaheuristics are used as very good optimization methods and they imitate natural, biologic, social and cultural process. In this work, we evaluate and compare three different metaheuristics which are population-based: Genetic Algorithms, CHC and Scatter Search. They work with a set of solutions in contrast to trajectory-based metaheuristics which use an only solution. From a comparative analysis, we can infer that Genetic Algorithms and CHC algorithms can solve satisfactorily problems with a growing complexity. While Scatter Search provides high quality solutions but its computational effort is very high too. en
dc.language en es
dc.subject Heuristic methods es
dc.subject Algorithms es
dc.subject Biology and genetics es
dc.title A phenotypic analysis of three population-based metaheuristics en
dc.type Objeto de conferencia es
sedici.creator.person Orellana, Alina es
sedici.creator.person Minetti, Gabriela F. es
sedici.description.note Workshop de Agentes y Sistemas Inteligentes (WASI) 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 2008-10
sedici.relation.event XIV 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)