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dc.creatorNebro, Antonio J.es
dc.creatorLópez Ibáñez, Manueles
dc.creatorBarba González, Cristóbales
dc.creatorGarcía Nieto, José Manueles
dc.date.accessioned2021-05-20T09:51:09Z
dc.date.available2021-05-20T09:51:09Z
dc.date.issued2019
dc.identifier.citationNebro, A.J., López Ibáñez, M., Barba González, C. y García Nieto, J.M. (2019). Automatic Configuration of NSGA-II with jMetal and irace. En GECCO 2019: Genetic and Evolutionary Computation Conference (1374-1381), Prague, Czech Republic: ACM Digital Library.
dc.identifier.isbn978-1-4503-6748-6es
dc.identifier.urihttps://hdl.handle.net/11441/109099
dc.description.abstractjMetal is a Java-based framework for multi-objective optimization with metaheuristics providing, among other features, a wide set of algorithms that are representative of the state-of-the-art. Although it has become a widely used tool in the area, it lacks support for automatic tuning of algorithm parameter settings, which can prevent obtaining accurate Pareto front approximations, especially for inexperienced users. In this paper, we present a first approach to combine jMetal and irace, a package for automatic algorithm configuration; the NSGA-II is chosen as the target algorithm to be tuned. The goal is to facilitate the combined use of both tools to jMetal users to avoid wasting time in adjusting manually the parameters of the algorithms. Our proposal involves the definition of a new algorithm template for evolutionary algorithms, which allows the flexible composition of multi-objective evolutionary algorithms from a set of configurable components, as well as the generation of configuration files for adjusting the algorithm parameters with irace. To validate our approach, NSGA-II is tuned with a benchmark problems and compared with the same algorithm using standard settings, resulting in a new variant that shows a competitive behavior.es
dc.description.sponsorshipMinisterio de Educación y Ciencia TIN2017-86049-Res
dc.description.sponsorshipJunta de Andalucía P12-TIC-1519es
dc.formatapplication/pdfes
dc.format.extent8es
dc.language.isoenges
dc.publisherACM Digital Libraryes
dc.relation.ispartofGECCO 2019: Genetic and Evolutionary Computation Conference (2019), pp. 1374-1381.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMulti-objective optimizationes
dc.subjectMetaheuristicses
dc.subjectSoftware Toolses
dc.subjectAutomatic Algorithm Configurationes
dc.titleAutomatic Configuration of NSGA-II with jMetal and iracees
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificiales
dc.relation.projectIDTIN2017-86049-Res
dc.relation.projectIDP12-TIC-1519es
dc.relation.publisherversionhttps://dl.acm.org/doi/10.1145/3319619.3326832es
dc.identifier.doi10.1145/3319619.3326832es
dc.publication.initialPage1374es
dc.publication.endPage1381es
dc.eventtitleGECCO 2019: Genetic and Evolutionary Computation Conferencees
dc.eventinstitutionPrague, Czech Republices
dc.relation.publicationplaceNew York, USAes
dc.contributor.funderMinisterio de Educación y Ciencia (MEC). Españaes
dc.contributor.funderJunta de Andalucíaes

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