Particle swarm optimization performance on special linear programming problems

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dc.contributor.authorErdoğmuş, Pakize
dc.date.accessioned2020-04-30T23:20:34Z
dc.date.available2020-04-30T23:20:34Z
dc.date.issued2010
dc.departmentDÜ, Teknik Eğitim Fakültesi, Elektronik ve Bilgisayar Eğitimi Bölümüen_US
dc.descriptionWOS: 000279559900013en_US
dc.description.abstractLinear programming (LP) is one of the best known optimization problems solved generally with Simplex Method. Most of the real life problems have been modeled as LP. The solutions of some special LP problems exhibiting cycling have not been studied except for the classical methods. This study, aimed to solve some special LP problems, exhibit cycling with Particle Swarm Optimization (PSO) and to show PSO performance for these problems. So, some special problems taken from literature have been solved with PSO. Results taken from Genetic Algorithm (GA) and PSO have been compared with the reference. The results have shown that PSO performance is generally better than GA in view of optimality and solution time. And it is also proposed that cycling problems are used for testing the performance of new developed algorithms like Numerical Benchmark Functions.en_US
dc.identifier.endpage1518en_US
dc.identifier.issn1992-2248
dc.identifier.issue12en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1506en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12684/4035
dc.identifier.volume5en_US
dc.identifier.wosWOS:000279559900013en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherAcademic Journalsen_US
dc.relation.ispartofScientific Research And Essaysen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLPen_US
dc.subjectcyclingen_US
dc.subjectPSOen_US
dc.titleParticle swarm optimization performance on special linear programming problemsen_US
dc.typeArticleen_US

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