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dc.contributor.authorSedenka, V.
dc.contributor.authorRaida, Zbyněk
dc.date.accessioned2016-03-11T09:19:17Z
dc.date.available2016-03-11T09:19:17Z
dc.date.issued2010-09cs
dc.identifier.citationRadioengineering. 2010, vol. 19, č. 3, s. 369-377. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/57006
dc.description.abstractThe paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB. Attention is turned to an elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel multi-objective Particle Swarm Optimization (PSO). The performance of optimizers is compared on three different test functions and on a cavity resonator synthesis. The microwave resonator is modeled using the Finite Element Method (FEM). The hit rate and the quality of the Pareto front distribution are classified.en
dc.formattextcs
dc.format.extent369-377cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2010/10_03_369_377.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectMulti-objective optimizationen
dc.subjectbinary genetic algorithmen
dc.subjectparticle swarm optimizationen
dc.subjectPareto fronten
dc.subjectfinite element method.en
dc.titleCritical Comparison of Multi-objective Optimization Methods: Genetic Algorithms versus Swarm Intelligenceen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue3cs
dc.coverage.volume19cs
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Except where otherwise noted, this item's license is described as Creative Commons Attribution 3.0 Unported License