Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/28174
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dc.date.accessioned2022-08-11T12:28:19Z-
dc.date.available2022-08-11T12:28:19Z-
dc.date.issued2007-10-
dc.identifier.citationYıldız, A. R. (2007). "Hybrid multi-objective shape design optimization using Taguchi's method and genetic algorithm". Structural and Multidisciplinary Optimization, 34(4), 317-332.en_US
dc.identifier.issn16151488-
dc.identifier.urihttps://doi.org/10.1007/s00158-006-0079-x-
dc.identifier.urihttps://link.springer.com/article/10.1007%2Fs00158-006-0079-x-
dc.identifier.urihttp://hdl.handle.net/11452/28174-
dc.description.abstractThis research is based on a new hybrid approach, which deals with the improvement of shape optimization process. The objective is to contribute to the development of more efficient shape optimization approaches in an integrated optimal topology and shape optimization area with the help of genetic algorithms and robustness issues. An improved genetic algorithm is introduced to solve multi-objective shape design optimization problems. The specific issue of this research is to overcome the limitations caused by larger population of solutions in the pure multi-objective genetic algorithm. The combination of genetic algorithm with robust parameter design through a smaller population of individuals results in a solution that leads to better parameter values for design optimization problems. The effectiveness of the proposed hybrid approach is illustrated and evaluated with test problems taken from literature. It is also shown that the proposed approach can be used as first stage in other multi-objective genetic algorithms to enhance the performance of genetic algorithms. Finally, the shape optimization of a vehicle component is presented to illustrate how the present approach can be applied for solving multi-objective shape design optimization problems.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGenetic algorithmsen_US
dc.subjectMulti-objective optimizationen_US
dc.subjectShape optimizationen_US
dc.subjectTaguchi's methoden_US
dc.subjectTopology optimizationen_US
dc.subjectStructural optimizationen_US
dc.subjectNeural-networken_US
dc.subjectSearchen_US
dc.subjectParameter estimationen_US
dc.subjectRobust parametersen_US
dc.subjectShape optimizationen_US
dc.subjectVehicle componentsen_US
dc.subjectGenetic algorithmsen_US
dc.subjectMultiobjective optimizationen_US
dc.subjectProblem solvingen_US
dc.subjectTaguchi methodsen_US
dc.titleHybrid multi-objective shape design optimization using Taguchi's method and genetic algorithmen_US
dc.typeArticleen_US
dc.identifier.wos000255419500003tr_TR
dc.identifier.scopus2-s2.0-34548222738tr_TR
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergitr_TR
dc.contributor.departmentUludağ Üniversitesi/Mühendislik Fakültesi.tr_TR
dc.contributor.orcid0000-0002-8297-0777tr_TR
dc.contributor.orcid0000-0003-1790-6987tr_TR
dc.identifier.startpage317tr_TR
dc.identifier.endpage332tr_TR
dc.identifier.volume34tr_TR
dc.identifier.issue4tr_TR
dc.relation.journalStructural and Multidisciplinary Optimizationen_US
dc.contributor.buuauthorYıldız, Ali Rıza-
dc.contributor.buuauthorÖztürk, Nursel-
dc.contributor.buuauthorKaya, Necmettin-
dc.contributor.buuauthorÖztürk, Ferruh-
dc.contributor.researcheridAAG-9336-2021tr_TR
dc.contributor.researcheridR-4929-2018tr_TR
dc.contributor.researcheridF-7426-2011tr_TR
dc.contributor.researcheridAAG-9923-2021tr_TR
dc.subject.wosComputer science, interdisciplinary applicationsen_US
dc.subject.wosEngineering, multidisciplinaryen_US
dc.subject.wosMechanicsen_US
dc.indexed.wosSCIEen_US
dc.indexed.scopusScopusen_US
dc.wos.quartileQ2 (Engineering, multidisciplinary)en_US
dc.wos.quartileQ3en_US
dc.contributor.scopusid7102365439tr_TR
dc.contributor.scopusid7005688805tr_TR
dc.contributor.scopusid7005013334tr_TR
dc.contributor.scopusid56271685800tr_TR
dc.subject.scopusMachining; Chatter; Turningen_US
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