In 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
Notas
VII Workshop de Agentes y Sistemas Inteligentes (WASI)
Información general
Fecha de exposición:octubre 2006
Fecha de publicación:octubre 2006
Idioma del documento:Inglés
Evento:XII Congreso Argentino de Ciencias de la Computación
Institución de origen:Red de Universidades con Carreras en Informática (RedUNCI)
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)