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Introducing a Robust and Efficient Stopping Criterion for MOEA's

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Inteligencia Artificial Aplicada (GIAA)es
dc.contributor.authorGuerrero Madrid, José Luis
dc.contributor.authorMartí, Luis
dc.contributor.authorBerlanga de Jesús, Antonio
dc.contributor.authorGarcía, Jesús
dc.contributor.authorMolina López, José Manuel
dc.date.accessioned2014-03-04T11:54:26Z
dc.date.available2014-03-04T11:54:26Z
dc.date.issued2010
dc.descriptionProceedings of: IEEE World Congress on Computational Intelligence 2010 (WCCI 2010): IEEE Congress on Evolutionary Computation (CEC 2010). Barcelona, Spain, 18-23 July 2010.es
dc.description.abstractSoft computing methods, and Multi-Objective Evolutionary Algorithms (MOEAs) in particular, lack a general convergence criterion which prevents these algorithms from detecting the generation where further evolution will provide little improvements (or none at all) over the current solution, making them waste computational resources. This paper presents the Least Squares Stopping Criterion (LSSC), an easily configurable and implementable, robust and efficient stopping criterion, based on simple statistical parameters and residue analysis, which tries to introduce as few setup parameters as possible, being them always related to the MOEAs research field rather than the techniques applied by the criterion.es
dc.description.sponsorshipThis work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC- 1485) and DPS2008-07029-C02-02es
dc.description.statusPublicadoes
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationIEEE Congress on Evolutionary Computation (CEC 2010). Barcelona, Spain, 18-23 July 2010. IEEE, pp. 4314-4321.es
dc.identifier.doi10.1109/CEC.2010.5586265
dc.identifier.isbn978-1-4244-6909-3
dc.identifier.publicationfirstpage4314
dc.identifier.publicationlastpage4321
dc.identifier.publicationtitleIEEE Congress on Evolutionary Computation (CEC 2010). Barcelona, Spain, 18-23 July 2010.
dc.identifier.urihttps://hdl.handle.net/10016/18411
dc.identifier.uxxiCC/0000011617
dc.language.isoenges
dc.publisherIEEE - The Institute Of Electrical And Electronics Engineers, Inces
dc.relation.eventdate18-23 July, 2010es
dc.relation.eventplaceBarcelonaes
dc.relation.eventtitleIEEE World Congress on Computational Intelligence 2010 (WCCI 2010): IEEE Congress on Evolutionary Computation (CEC 2010).es
dc.relation.projectIDComunidad de Madrid. S2009/TIC-1485/CONTEXTSes
dc.rights© 2010 IEEEes
dc.rights.accessRightsopen accesses
dc.subject.ecienciaInformáticaes
dc.subject.otherRobust and efficient stopping criteriones
dc.subject.otherMOEAses
dc.subject.otherLSSCes
dc.subject.otherMulti-Objective Evolutionary Algorithmses
dc.subject.otherLeast Squares Stopping Criterionen
dc.titleIntroducing a Robust and Efficient Stopping Criterion for MOEA'ses
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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