Optimum design of cold-formed steel frames via five novel nature-inspired metaheuristic algorithms under consideration of seismic loading

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dc.authoridCARBAS, SERDAR/0000-0002-3612-0640
dc.contributor.authorCarbas, Serdar
dc.contributor.authorArtar, Musa
dc.date.accessioned2024-10-04T18:52:34Z
dc.date.available2024-10-04T18:52:34Z
dc.date.issued2021
dc.departmentBayburt Üniversitesien_US
dc.description.abstractIn this paper, an unbiased comparative assessment scheme for algorithmic performances of five novel nature-inspired metaheuristic algorithms in design optimization of steel frames made out of cold-formed steel sections under consideration of seismic loading is presented. These contemporary algorithms are so-called tree seed, squirrel search, water strider, grey wolf, and brain storm optimization. The functionality of the proposed algorithms is appraised with respect to design precisions in both portal and space cold-formed steel frames formulated according to the design provisions implemented by AISI-LRFD (American Iron and Steel Institute-Load and Resistance Factor Design). The cross-sectional dimensions of steel profiles, which are selected from available set of cold-formed thin-walled single-C sections, are treated as design variables in the optimization process in order to minimize the structural weight of the frames. In addition to specification constraint requirements, lateral and vertical displacement restrictions of the structural elements required for stability of the frames are also taken into account. Design optimization algorithms necessitate the structural response of cold-formed steel frames under load combinations including seismic loading effects which is accomplished by utilizing the open application programming interface (OAPI) mastery of MATLAB with SAP2000. The design optimization of cold-formed steel frames that is a discrete nonlinear programming problem reveal the robustness and applicability of proposed contemporary nature-inspired metaheuristic algorithms in real-sized complex structural optimization problems.en_US
dc.identifier.doi10.1016/j.istruc.2021.06.096
dc.identifier.endpage4030en_US
dc.identifier.issn2352-0124
dc.identifier.scopus2-s2.0-85110235986en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage4011en_US
dc.identifier.urihttps://doi.org/10.1016/j.istruc.2021.06.096
dc.identifier.urihttp://hdl.handle.net/20.500.12403/3563
dc.identifier.volume33en_US
dc.identifier.wosWOS:000701936600002en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Science Incen_US
dc.relation.ispartofStructuresen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCold-formed steel framesen_US
dc.subjectStructural optimizationen_US
dc.subjectOptimum designen_US
dc.subjectNature-inspired metaheuristic algorithmsen_US
dc.subjectSeismic loadingen_US
dc.subjectAISI-LRFDen_US
dc.titleOptimum design of cold-formed steel frames via five novel nature-inspired metaheuristic algorithms under consideration of seismic loadingen_US
dc.typeArticleen_US

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