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Statistical analysis of a multi-objective optimization algorithm based on a model of particles with vorticity behavior

dc.contributor.authorMeza, Joaquín
dc.contributor.authorEspitia, Helbert
dc.contributor.authorMontenegro, Carlos Enrique
dc.contributor.authorGonzález-Crespo, Rubén
dc.date2016-09
dc.date.accessioned2017-10-26T14:51:36Z
dc.date.available2017-10-26T14:51:36Z
dc.identifier.issn1433-7479
dc.identifier.urihttps://reunir.unir.net/handle/123456789/5846
dc.description.abstractIn this paper, a strategy for multi-objective optimization based upon the behavior of a particle swarm with rotational and linear motion is presented. The strategy for multi-objective optimization is based upon the emulation of the linear and circular movements of a swarm (flock). Thus emerges the physical basis for the cognitive model, which in conjunction with exploration-exploitation results in the proposal of a cognitive algorithm, which is tested through several multi-objective optimization functions. The algorithm proposed is compared with standard particle swarm optimization multi-objective via statistical analysis.es_ES
dc.language.isoenges_ES
dc.publisherSoft Computinges_ES
dc.relation.ispartofseriesnúmero especial;vol. 20, nº 9
dc.relation.urihttps://link.springer.com/article/10.1007%2Fs00500-015-1972-2es_ES
dc.rightsrestrictedAccesses_ES
dc.subjectmulti-objective optimizationes_ES
dc.subjectparticle swarmes_ES
dc.subjectvorticityes_ES
dc.subjectJCRes_ES
dc.subjectScopuses_ES
dc.titleStatistical analysis of a multi-objective optimization algorithm based on a model of particles with vorticity behaviores_ES
dc.typeArticulo Revista Indexadaes_ES
reunir.tag~ARIes_ES
dc.identifier.doihttp://dx.doi.org/10.1007/s00500-015-1972-2


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