dc.creatorAragón, Victoria S.
dc.creatorEsquivel, Susana Cecilia
dc.creatorCoello Coello, Carlos
dc.date2006-10
dc.date2006-10
dc.date2012-10-18T18:22:48Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/22628
dc.descriptionIn this paper, we present an artifi cial immune system (AIS) based on the CLONALG algorithm for solving constrained (numerical) optimization problems. We develop a new mutation operator which produces large and small step sizes and which aims to provide better exploration capabilities. We validate our proposed approach with 13 test functions taken from the specialized literature and we compare our results with respect to Stochastic Ranking (which is an approach representative of the state-of-the-art in the area) and with respect to an AIS previously proposed by one of the co-authors
dc.descriptionVII Workshop de Agentes y Sistemas Inteligentes (WASI)
dc.descriptionRed de Universidades con Carreras en Informática (RedUNCI)
dc.formatapplication/pdf
dc.format1197-1207
dc.languageen
dc.relationXII Congreso Argentino de Ciencias de la Computación
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.subjectCiencias Informáticas
dc.titleArtificial immune system for solving constrained optimization problems
dc.typeObjeto de conferencia
dc.typeObjeto de conferencia


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