R2-Based Multi/Many-Objective Particle Swarm Optimization

AudienciaPúblico en generales_ES
CoberturaMéxicoes_ES
Fecha de ingreso2026-09-15T00:30:02Z
Fecha de publicación2016-01-01
ResumenWe propose to couple theR2performance measure and Particle Swarm Optimization in order to handle multi/many-objective problems. Our proposal shows that through a well-designed interaction process we could maintain the metaheuristic almost inalterable and through theR2performance measure we did not use neither an external archive nor Pareto dominance to guide the search. The proposed approach is validated using several test problems and performance measures commonly adopted in the specialized literature. Results indicate that the proposed algorithm produces results that are competitive with respect to those obtained by four well-known MOEAs. Additionally, we validate our proposal in many-objective optimization problems. In these problems, our approach showed its main strength, since it could outperform another well-known indicator-based MOEA.es_ES
Doihttps://doi.org/10.1155/2016/1898527es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/1986
Idiomaeses_ES
EditorialWileyes_ES
RelaciónComputational Intelligence and Neurosciencees_ES
URL relacionadohttps://doi.org/10.1155/2016/1898527es_ES
DerechosAcceso abierto (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_abf2es_ES
FuenteComputational Intelligence and Neuroscience
TítuloR2-Based Multi/Many-Objective Particle Swarm Optimizationes_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 páginas1-10es_ES
URL relacionadahttps://doi.org/10.1155/2016/1898527
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen2016es_ES

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