Artificial Immune System for Solving Constrained Optimization Problems
In this paper, we present an artificial immune system (AIS) based on the CLONALG algorithm for solvingconstrained (numerical) optimization problems. We develop a new mutation operator which produces largeand small step sizes and which aims to provide better exploration capabilities. We validate our...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2007 |
| País: | México |
| Institución: | Instituto Politécnico Nacional |
| Repositorio: | Redalyc-IPN |
| OAI Identifier: | oai:redalyc.org:92503506 |
| Acceso en línea: | https://www.redalyc.org/articulo.oa?id=92503506 |
| Access Level: | acceso abierto |
| Palabra clave: | Ingeniería Artificial Immune System Constrained Optimization Problems |
| Sumario: | In this paper, we present an artificial immune system (AIS) based on the CLONALG algorithm for solvingconstrained (numerical) optimization problems. We develop a new mutation operator which produces largeand small step sizes and which aims to provide better exploration capabilities. We validate our proposedapproach with 13 test functions taken from the specialized literature and we compare our results withrespect to Stochastic Ranking (which is an approach representative of the state-of-the-art in the area) andwith respect to an AIS previously proposed by one of the co-authors. |
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