Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/54334
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dc.contributor.authorWinter Althaus, Gabrielen_US
dc.contributor.authorGalván González, Blas Joséen_US
dc.contributor.authorGonzalez, B.en_US
dc.contributor.authorJiménez Fránquiz, Juan Ignacioen_US
dc.contributor.authorGreiner Sánchez, David Juanen_US
dc.contributor.otherGreiner, David-
dc.date.accessioned2019-02-18T10:08:20Z-
dc.date.available2019-02-18T10:08:20Z-
dc.date.issued2005en_US
dc.identifier.issn1432-7643en_US
dc.identifier.urihttp://hdl.handle.net/10553/54334-
dc.description.abstractSince it has currently became essential to design more efficient and robust alternative techniques to solve hard optimisation problems in industry or science, and of easy use for practitioners, here a new way of developing simple Artificial Intelligence based Evolutionary Algorithms will be introduced. Our evolutionary computational implementation is a new idea in optimisation. Any evolutionary operators and their associated parameters from well-established evolutionary methods can be considered in such a way that the entire algorithm or intelligent agent-based software performs with very high efficiency without a prior need to investigate which method will be the best for a given optimisation problem.The implementation presented, named Flexible Evolution (FE), has capacity to adapt the operators, the parameters and the algorithm to the circumstances faced at each step of every optimisation run and is able to take into account lessons learned by different research works in the adaptation of operators and parameters. The FE uses Artificial Intelligence concepts to manage internal procedures to adopt decisions and correct the wrong ones. Our aim in this paper will be to give the keys to design these types of procedures, and more specifically, to find the way of achieving an optimum performance of the operators involved in the search, in our case by means of a function included in our algorithm called Sampling Engine. An early implementation has been already developed and tested in our previous works [66–68], so in this paper, new results of a second software implementation are presented comparing the results with those obtained by other methods, using well-known hard test functions.en_US
dc.languageengen_US
dc.relation.ispartofSoft Computingen_US
dc.sourceSoft Computing [ISSN 1432-7643], v. 9 (4), p. 299-323en_US
dc.subject3313 Tecnología e ingeniería mecánicasen_US
dc.subject120304 Inteligencia artificialen_US
dc.subject1206 Análisis numéricoen_US
dc.subject.otherFlexible evolution (FE)en_US
dc.subject.otherEvolutionary algorithmsen_US
dc.subject.otherSampling engineen_US
dc.titleA flexible evolutionary agent: cooperation and competition among real-coded evolutionary operatorsen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s00500-004-0381-8
dc.identifier.scopus14844353141-
dc.identifier.scopus2-s2.0-14844353141-
dc.identifier.isi000228332600007-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
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dc.contributor.orcid#NODATA#-
dc.contributor.authorscopusid7202988477-
dc.contributor.authorscopusid8704390300-
dc.contributor.authorscopusid57201809923-
dc.contributor.authorscopusid55643744700
dc.contributor.authorscopusid25631597900-
dc.contributor.authorscopusid7402489561-
dc.contributor.authorscopusid56268125800-
dc.description.lastpage323-
dc.identifier.issue4-
dc.description.firstpage299-
dc.relation.volume9-
dc.investigacionCienciasen_US
dc.type2Artículoen_US
dc.identifier.wosWOS:000228332600007-
dc.contributor.daisngid1266063-
dc.contributor.daisngid7728459-
dc.contributor.daisngid1678121
dc.contributor.daisngid77949-
dc.contributor.daisngid6941565
dc.contributor.daisngid7321859-
dc.contributor.daisngid30368546
dc.contributor.daisngid2653510-
dc.contributor.daisngid1559703-
dc.identifier.investigatorRIDN-8557-2013-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Winter, G
dc.contributor.wosstandardWOS:Galvan, B
dc.contributor.wosstandardWOS:Alonso, S
dc.contributor.wosstandardWOS:Gonzalez, B
dc.contributor.wosstandardWOS:Jimenez, JI
dc.contributor.wosstandardWOS:Greiner, D
dc.date.coverdateAbril 2005
dc.identifier.ulpgces
dc.description.jcr0,538
dc.description.jcrqQ3
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptSIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptMatemáticas-
crisitem.author.deptSIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptSIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptMatemáticas-
crisitem.author.deptSIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptMatemáticas-
crisitem.author.orcid0000-0002-7915-0655-
crisitem.author.orcid0000-0002-7915-0655-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameWinter Althaus, Gabriel-
crisitem.author.fullNameGalván González, Blas José-
crisitem.author.fullNameGonzález Landín, Begoña-
crisitem.author.fullNameGonzález Landín, Begoña-
crisitem.author.fullNameJiménez Fránquiz, Juan Ignacio-
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