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An Effective Robust Optimization Based on Genetic Algorithm

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An Effective Robust Optimization Based on Genetic Algorithm
Id. 44849095
Idioma inglés
Titulo An Effective Robust Optimization Based on Genetic Algorithm
Autor(es) Maruyama, Takayuki
Igarashi, Hajime
Localización http://hdl.handle.net/2115/38721
IEEE Transactions on Magnetics. 44(6), 2008, 990-993
http://dx.doi.org/10.1109/TMAG.2007.916696
Versión 1.0
Estado Final
Descripción Although probabilistic optimization methods based on genetic algorithm (GA) provides accurate results, its performance is sometimes considerably sensitive to parameter changes. Moreover, the constraints are violated due to such parameter changes. A robust GA which performs random perturbation during optimization processes has been applied to some mathematical problems to show that it works as fast as the usual GAs. An adequate elite reservation technique for the robust GA is presented and applied to the robust GA for electromagnetic problems. Moreover, this method is shown to find solutions which are kept feasible against parameter changes.
Palabras clave constraint condition
Tipo de recurso article
Tipo de Interactividad Expositivo
Nivel de Interactividad muy bajo
Audiencia Estudiante
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Estructura Atomic
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Copyright
© 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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Fecha de contribución 19-sep-2009
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