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dc.contributor.authorAldana Martín, José Francisco
dc.contributor.authorDurillo, Juan J.
dc.contributor.authorNebro-Urbaneja, Antonio Jesús 
dc.date.accessioned2023-11-13T12:32:55Z
dc.date.available2023-11-13T12:32:55Z
dc.date.created2023-11-13
dc.date.issued2023-10-10
dc.identifier.citationAldana-Martín, J. F., Durillo, J. J., & Nebro, A. J. (2023). Evolver: Meta-optimizing multi-objective metaheuristics. SoftwareX, 24, 101551. https://doi.org/10.1016/j.softx.2023.101551es_ES
dc.identifier.urihttps://hdl.handle.net/10630/28010
dc.description.abstractEvolver is a tool based on the formulation of the automatic configuration and design of multi-objective metaheuristics as a multi-objective optimization problem that can be solved by using the same kind of algorithms; i.e., we are applying a meta-optimization approach. Evolver provides highly configurable implementations of representative multi-objective solvers which can be automatically configured from a number of multi-objective problems used as the training set and a list of quality indicators which are the objectives to be optimized. Our tool is based on the jMetal framework, so a large number of existing algorithms can be used as meta-optimizers. A graphical user interface allows scientists to easily define auto-configuration scenarios, thus simplifying the complex process of finding high-quality algorithm settings.es_ES
dc.description.sponsorshipPartial funding for open access: Universidad de Málaga / CBUAes_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectOptimización matemáticaes_ES
dc.subjectProgramación heurísticaes_ES
dc.subject.otherMulti-objective optimizationes_ES
dc.subject.otherMetaheuristics auto-configuration and auto-designes_ES
dc.subject.otherFrameworkes_ES
dc.subject.otherjMetales_ES
dc.titleEvolver: Meta-optimizing multi-objective metaheuristics.es_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.identifier.doi10.1016/j.softx.2023.101551
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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