Hybrid tabu search algorithm for weight optimization of planar steel frames

MakaleAçık ErişimScopus SJRQ2

Özet

In this study, a hybrid metaheuristic algorithm called Hybrid Tabu Search (HTS) is proposed for the weight optimization of planar steel structures. The effectiveness of HTS lies in improving the initial conditions of a tabu search algorithm with a greedy search algorithm and a swap operator used in the phase of section selection. The effectiveness of the proposed method is tested and validated on three different benchmark examples. C♯ software is developed to perform the structural analyses. Numerical results obtained by using HTS showed that the proposed method achieved significantly lighter frame weights in most of the benchmark examples. When the method was examined in terms of computational efficiency, HTS was at a level that can compete with other algorithms examined within this study, although it did not provide a significant advantage.

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AlanDeğerDil
dc.contributor.authorTayfur, Bilal
dc.contributor.authorYilmaz, Hamid
dc.contributor.authorDaloğlu, Ayşe T.
dc.date.accessioned2026-10-29T19:10:54.398142394Z
dc.date.available2026-10-29T19:10:54.398142394Z
dc.date.issued2021
dc.description.abstractIn this study, a hybrid metaheuristic algorithm called Hybrid Tabu Search (HTS) is proposed for the weight optimization of planar steel structures. The effectiveness of HTS lies in improving the initial conditions of a tabu search algorithm with a greedy search algorithm and a swap operator used in the phase of section selection. The effectiveness of the proposed method is tested and validated on three different benchmark examples. C♯ software is developed to perform the structural analyses. Numerical results obtained by using HTS showed that the proposed method achieved significantly lighter frame weights in most of the benchmark examples. When the method was examined in terms of computational efficiency, HTS was at a level that can compete with other algorithms examined within this study, although it did not provide a significant advantage.
dc.identifier.doi10.1080/0305215x.2020.1793977
dc.identifier.eissn1029-0273
dc.identifier.endpage1383
dc.identifier.issn0305-215X
dc.identifier.issue8
dc.identifier.scopus2-s2.0-85088592520
dc.identifier.startpage1369
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/bayburt/13399
dc.identifier.volume53
dc.identifier.wosWOS:000552530700001
dc.language.isoen
dc.publisherTaylor and Francis Ltd.
dc.relation.ispartofEngineering Optimization
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjecthybrid tabu search algorithm
dc.subjectOptimization
dc.subjectplanar steel frames
dc.subject.classificationEngineering, Multidisciplinary
dc.subject.classificationOperations Research & Management Science
dc.subject.classificationEngineering
dc.subject.otherC (programming language)
dc.subject.otherLearning algorithms
dc.subject.otherNumerical methods
dc.subject.otherTabu search
dc.subject.otherGreedy search algorithms
dc.subject.otherHybrid metaheuristic algorithms
dc.subject.otherHybrid tabu search
dc.subject.otherInitial conditions
dc.subject.otherNumerical results
dc.subject.otherPlanar steel frames
dc.subject.otherTabu search algorithms
dc.subject.otherWeight optimization
dc.subject.otherComputational efficiency
dc.titleHybrid tabu search algorithm for weight optimization of planar steel frames
dc.typeArticle
rdl.citation.openalex15
rdl.citation.scopus17
rdl.citation.wos15
rdl.oa.statusclosed
rdl.oa.statuspreprint
rdl.oa.statusgreen
rdl.oa.urlhttp://hdl.handle.net/20.500.12403/3374
rdl.scopus.quartileQ2
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)