A Review of Surrogate Assisted Multiobjective Evolutionary Algorithms

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AudienciaPúblico en generales_ES
CoberturaMéxicoes_ES
Fecha de ingreso2026-09-15T00:30:02Z
Fecha de publicación2016-01-01
ResumenMultiobjective evolutionary algorithms have incorporated surrogate models in order to reduce the number of required evaluations to approximate the Pareto front of computationally expensive multiobjective optimization problems. Currently, few works have reviewed the state of the art in this topic. However, the existing reviews have focused on classifying the evolutionary multiobjective optimization algorithms with respect to the type of underlying surrogate model. In this paper, we center our focus on classifying multiobjective evolutionary algorithms with respect to their integration with surrogate models. This interaction has led us to classify similar approaches and identify advantages and disadvantages of each class.es_ES
Doihttps://doi.org/10.1155/2016/9420460es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/1985
Idiomaeses_ES
EditorialHindawi Limitedes_ES
RelaciónComputational Intelligence and Neurosciencees_ES
URL relacionadohttps://doi.org/10.1155/2016/9420460es_ES
DerechosAcceso abierto (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_abf2es_ES
FuenteComputational Intelligence and Neuroscience
TítuloA Review of Surrogate Assisted Multiobjective Evolutionary Algorithmses_ES
TipoArtículoes_ES
ArbitradoHa sido Arbitradoes_ES
AutorDíaz-Manríquez, Alan
AutorToscano, Gregorio
AutorBarron-Zambrano, Jose Hugo
AutorTello-Leal, Edgar
AutorDíaz-Manríquez, Alanes_ES
AutorToscano, Gregorioes_ES
AutorBarron-Zambrano, Jose Hugoes_ES
AutorTello-Leal, Edgares_ES
InstituciónUniversidad Autónoma de Tamaulipas
InstituciónUniversidad Autónoma de Tamaulipases_ES
Rango de páginas1-14es_ES
URL relacionadahttps://doi.org/10.1155/2016/9420460
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen2016es_ES

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