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dc.contributor.authorTsoulos, I. G.en
dc.contributor.authorLagaris, I. E.en
dc.date.accessioned2015-11-24T17:01:25Z-
dc.date.available2015-11-24T17:01:25Z-
dc.identifier.issn0010-4655-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/10922-
dc.rightsDefault Licence-
dc.subjectglobal optimizationen
dc.subjectstochastic methodsen
dc.subjectgenetic programmingen
dc.subjectgrammatical evolutionen
dc.subjectalgorithmen
dc.subjectminimaen
dc.titleGenetically controlled random search: a global optimization method for continuous multidimensional functionsen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDOI 10.1016/j.cpc.2005.09.007-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικήςel
heal.publicationDate2006-
heal.abstractA new stochastic method for locating the global mini mum of a multidimensional function inside a rectangular hyperbox is presented. A sampling technique is employed that makes use of the procedure known as grammatical evolution. The method can be considered as a "genetic" modification of the Controlled Random Search procedure due to Price. The user may code the objective function either in C++ or in Fortran 77. We offer a comparison of the new method with others of similar structure, by presenting results of computational experiments on a set of test functions.en
heal.journalNameComputer Physics Communicationsen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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