Differential evolution and simulated annealing algorithms for mechanical systems design

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dc.contributor.authorSaruhan, Hamit
dc.date.accessioned2020-04-30T13:32:19Z
dc.date.available2020-04-30T13:32:19Z
dc.date.issued2014
dc.departmentDÜ, Mühendislik Fakültesi, Makine Mühendisliği Bölümüen_US
dc.description.abstractIn this study, nature inspired algorithms – the Differential Evolution (DE) and the Simulated Annealing (SA) – are utilized to seek a global optimum solution for ball bearings link system assembly weight with constraints and mixed design variables. The Genetic Algorithm (GA) and the Evolution Strategy (ES) will be a reference for the examination and validation of the DE and the SA. The main purpose is to minimize the weight of an assembly system composed of a shaft and two ball bearings. Ball bearings link system is used extensively in many machinery applications. Among mechanical systems, designers pay great attention to the ball bearings link system because of its significant industrial importance. The problem is complex and a time consuming process due to mixed design variables and inequality constraints imposed on the objective function. The results showed that the DE and the SA performed and obtained convergence reliability on the global optimum solution. So the contribution of the DE and the SA application to the mechanical system design can be very useful in many real-world mechanical system design problems. Beside, the comparison confirms the effectiveness and the superiority of the DE over the others algorithms – the SA, the GA, and the ES – in terms of solution quality. The ball bearings link system assembly weight of 634,099 gr was obtained using the DE while 671,616 gr, 728213.8 gr, and 729445.5 gr were obtained using the SA, the ES, and the GA respectively. © 2014 Karabuk Universityen_US
dc.identifier.doi10.1016/j.jestch.2014.04.006en_US
dc.identifier.endpage136en_US
dc.identifier.issn2215-0986
dc.identifier.issue3en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage131en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.jestch.2014.04.006
dc.identifier.urihttps://hdl.handle.net/20.500.12684/228
dc.identifier.volume17en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier B.V.en_US
dc.relation.ispartofEngineering Science and Technology, an International Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectDesign optimization; Differential evolution; Genetic algorithm; Simulated annealingen_US
dc.titleDifferential evolution and simulated annealing algorithms for mechanical systems designen_US
dc.typeArticleen_US

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