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dc.contributor.authorPetalas, Y. G.en
dc.contributor.authorParsopoulos, K. E.en
dc.contributor.authorVrahatis, M. N.en
dc.date.accessioned2015-11-24T17:01:36Z-
dc.date.available2015-11-24T17:01:36Z-
dc.identifier.issn0254-5330-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/10951-
dc.rightsDefault Licence-
dc.subjectglobal optimizationen
dc.subjectparticle swarm optimizationen
dc.subjectmemetic algorithmsen
dc.subjectlocal searchen
dc.subjectfuzzy cognitive mapsen
dc.subjectconvergenceen
dc.subjectcomputationen
dc.subjectalgorithmsen
dc.subjectselectionen
dc.subjectevolutionen
dc.subjectdesignen
dc.titleMemetic particle swarm optimizationen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDOI 10.1007/s10479-007-0224-y-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικήςel
heal.publicationDate2007-
heal.abstractWe propose a new Memetic Particle Swarm Optimization scheme that incorporates local search techniques in the standard Particle Swarm Optimization algorithm, resulting in an efficient and effective optimization method, which is analyzed theoretically. The proposed algorithm is applied to different unconstrained, constrained, minimax and integer programming problems and the obtained results are compared to that of the global and local variants of Particle Swarm Optimization, justifying the superiority of the memetic approach.en
heal.journalNameAnnals of Operations Researchen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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