Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/72378
Campo DC Valoridioma
dc.contributor.authorSalazar Aponte, Daniel E.en_US
dc.contributor.authorRocco S, Claudio M.en_US
dc.contributor.authorGalván, Blasen_US
dc.date.accessioned2020-05-13T16:30:58Z-
dc.date.available2020-05-13T16:30:58Z-
dc.date.issued2010en_US
dc.identifier.isbn978-3-642-01019-4en_US
dc.identifier.issn0302-9743en_US
dc.identifier.otherScopus-
dc.identifier.otherWoS-
dc.identifier.urihttp://hdl.handle.net/10553/72378-
dc.description.abstractIn this article we present a methodological framework entitled 'Analysis of Uncertainty and Robustness in Evolutionary Optimization' or AUREO for short. This methodology was developed as a diagnosis tool to analyze the characteristics of the decision-making problems to be solved with Multi-Objective Evolutionary Algorithms (MOEA) in order to: 1) determine the mathematical program that represents best the current problem in terms of the available information, and 2) to help the design or adaptation of the MOEA meant to solve the mathematical program. Regarding the first point, the different versions of decision-making problems in the presence of uncertainty are reduced to a few classes, while for the second point possible configurations of MOEA are suggested in terms of the type of uncertainty and the theory used to represent it. Finally, the AUREO has been introduced and tested successfully in different applications in [1].en_US
dc.languageengen_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) [ISSN 0302-9743], v. 5467 LNCS, p. 51-65, (Diciembre 2010)en_US
dc.subject120304 Inteligencia artificialen_US
dc.subject.otherMultiobjective Optimizationen_US
dc.subject.otherMean-Valueen_US
dc.subject.otherVarianceen_US
dc.titleOn uncertainty and robustness in evolutionary optimization-based MCDMen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009en_US
dc.identifier.doi10.1007/978-3-642-01020-0_9en_US
dc.identifier.scopus78650742261-
dc.identifier.isi000265784100004-
dc.contributor.authorscopusid56240751500-
dc.contributor.authorscopusid7004508307-
dc.contributor.authorscopusid8704390300-
dc.identifier.eissn1611-3349-
dc.description.lastpage65en_US
dc.description.firstpage51en_US
dc.relation.volume5467 LNCSen_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.contributor.daisngid1400577-
dc.contributor.daisngid10849402-
dc.contributor.daisngid1678121-
dc.description.numberofpages4en_US
dc.identifier.eisbn978-3-642-01020-0-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Aponte, DE-
dc.contributor.wosstandardWOS:Rocco, CM-
dc.contributor.wosstandardWOS:Galvan, B-
dc.date.coverdateDiciembre 2010en_US
dc.identifier.conferenceidevents120670-
dc.identifier.ulpgces
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR SIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameGalvan Gonzalez,Blas Jose-
crisitem.event.eventsstartdate07-04-2009-
crisitem.event.eventsenddate10-04-2009-
Colección:Actas de congresos
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