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An improvement of genetic algorithm based on dynamic operators rates controlled by the population performance

dc.contributor.authorAzevedo, Beatriz Flamia
dc.contributor.authorPereira, Ana I.
dc.contributor.authorBressan, Glaucia
dc.date.accessioned2023-02-28T15:44:36Z
dc.date.available2023-02-28T15:44:36Z
dc.date.issued2020
dc.description.abstractThis work presents a hybrid approach of genetic algorithm with dynamic operators rates that adapt to the phases of the evolutionary process. The operator’s rates are controlled by the amplitude variation and standard deviation of the objective function. Besides, a new stopping criterion is presented to be used in conjunction with the proposed algorithm. The developed approach is tested with six optimization benchmark functions from the literature. The results are compared to the genetic algorithm with constant rates in terms of the number of function evaluations, the number of iterations, execution time and optimum solution analysis.pt_PT
dc.description.sponsorshipThis work has been supported by FCT — Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/5757/2020.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAzevedo, Beatriz Flamia; Pereira, Ana I.; Bressan, Glaucia (2020). An improvement of genetic algorithm based on dynamic operators rates controlled by the population performance. In 9th International Conference on Operations Research and Enterprise Systems, ICORES 2020. Valletapt_PT
dc.identifier.urihttp://hdl.handle.net/10198/27320
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectGenetic algorithmpt_PT
dc.subjectGenetic operatorspt_PT
dc.subjectDynamic ratespt_PT
dc.subjectHybrid approachpt_PT
dc.titleAn improvement of genetic algorithm based on dynamic operators rates controlled by the population performancept_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferencePlaceValletapt_PT
oaire.citation.title9th International Conference on Operations Research and Enterprise Systems, ICORES 2020pt_PT
person.familyNameAzevedo
person.familyNamePereira
person.givenNameBeatriz Flamia
person.givenNameAna I.
person.identifier.ciencia-id181E-855C-E62C
person.identifier.ciencia-id0716-B7C2-93E4
person.identifier.orcid0000-0002-8527-7409
person.identifier.orcid0000-0003-3803-2043
person.identifier.ridF-3168-2010
person.identifier.scopus-author-id15071961600
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication04fa4023-3726-4dd5-8d97-f6b162ceb820
relation.isAuthorOfPublicatione9981d62-2a2b-4fef-b75e-c2a14b0e7846
relation.isAuthorOfPublication.latestForDiscoverye9981d62-2a2b-4fef-b75e-c2a14b0e7846

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