dc.creatorMedeiros, Hudson Geovane de
dc.creatorGoldbarg, Elizabeth Ferreira Gouvêa
dc.creatorGoldbarg, Marco Cesar
dc.date2018-11-19
dc.date.accessioned2022-10-04T22:27:14Z
dc.date.available2022-10-04T22:27:14Z
dc.identifierhttps://seer.ufrgs.br/index.php/rita/article/view/RITA_Vol25_Nr4_11
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3870377
dc.descriptionAbstract: The optimization of multi-objective problems from the Pareto dominance viewpoint can lead to huge sets of incomparable solutions. Many heuristic techniques proposed to these problems have to deal with approximation sets that can be limited or not. Usually, a new solution generated by a heuristic is compared with other archived non-dominated solutions generated previously. Many techniques deal with limited size archives, since comparisons within unlimited archives may require significant computational effort. To maintain limited archives, solutions need to be discarded. Several techniques were proposed to deal with the problem of deciding which solutions remain in the archive and which are discarded. Previous investigations showed that those techniques might not prevent deterioration of the archives. In this study, we propose to store discarded solutions in a secondary archive and, periodically, recycle them, bringing them back to the optimization process. Three recycling techniques were investigated for three known methods. The datasets for the experiments consisted of 91 instances of discrete and continuous problems with 2, 3 and 4 objectives. The results showed that the recycling method can benefit the tested optimizers on many problem classes.pt-BR
dc.formatapplication/pdf
dc.languageeng
dc.publisherInstituto de Informática - Universidade Federal do Rio Grande do Sulen-US
dc.relationhttps://seer.ufrgs.br/index.php/rita/article/view/RITA_Vol25_Nr4_11/pdf
dc.rightsCopyright (c) 2018 Hudson Geovane de Medeiros, Elizabeth Ferreira Gouvêa Goldbarg, Marco Cesar Goldbargpt-BR
dc.sourceRevista de Informática Teórica e Aplicada; Vol. 25 No. 4 (2018); 11-27en-US
dc.sourceRevista de Informática Teórica e Aplicada; v. 25 n. 4 (2018); 11-27pt-BR
dc.source2175-2745
dc.source0103-4308
dc.subjectArchiving techniquespt-BR
dc.subjectMulti-objective evolutionary algorithmspt-BR
dc.subjectRecycling techniques.pt-BR
dc.titleInvestigation of Archiving Techniques for Evolutionary Multi-objective Optimizerspt-BR
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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