A novel hybrid global optimization algorithm having training strategy: hybrid Taguchi-vortex search algorithm

Basit Öğe Kaydı
dc.authoridTezcan, Suleyman Sungur/0000-0001-6846-8222
dc.authoridCOBAN, Melih/0000-0001-9528-7187
dc.authoridEKE, Ibrahim/0000-0003-4792-238X
dc.contributor.authorSaka, Mustafa
dc.contributor.authorCoban, Melih
dc.contributor.authorEke, Ibrahim
dc.contributor.authorTezcan, Suleyman Sungur
dc.contributor.authorTaplamacioglu, Muslum Cengiz
dc.date.accessioned2025-01-21T16:34:50Z
dc.date.available2025-01-21T16:34:50Z
dc.date.issued2021
dc.departmentKırıkkale Üniversitesi
dc.description.abstractIn this paper, a novel hybrid Taguchi-vortex search algorithm (HTVS) is proposed for solving global optimization problems. Taguchi orthogonal approximation and vortex search algorithm (VS) are hybridized in presenting method. In HTVS, orthogonal arrays in the Taguchi method are trained and obtained better solutions are used to find global optima in VS. Thus, HTVS has better relation between exploration and exploitation, and it exhibits more powerful approximation to find global optimum value. Proposed HTVS algorithm is applied to sixteen well-known benchmark optimization test functions with different dimensions. The results are compared with the Taguchi orthogonal array approximation (TOAA), vortex search algorithm, grey wolf optimizer (GWO), sine cosine algorithm (SCA), moth-flame optimization algorithm (MFO), whale optimization algorithm (WOA) and salp swarm algorithm (SSA). In order to compare the effectiveness of HTVS statistically, Wilcoxon signed-rank test (WSRT) is used in this study. Furthermore, HTVS is applied to two different real engineering problems having some constraints (tension/compression spring design and pressure vessel design). All obtained results suggested that HTVS can find optimal or very close to optimal results. Moreover, it has good computational ability and fast convergence behavior as well.
dc.identifier.doi10.3906/elk-2004-193
dc.identifier.endpage+
dc.identifier.issn1300-0632
dc.identifier.issn1303-6203
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85112715587
dc.identifier.scopusqualityQ2
dc.identifier.startpage1908
dc.identifier.trdizinid523774
dc.identifier.urihttps://doi.org/10.3906/elk-2004-193
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay523774
dc.identifier.urihttps://hdl.handle.net/20.500.12587/24003
dc.identifier.volume29
dc.identifier.wosWOS:000679321200004
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.publisherTubitak Scientific & Technological Research Council Turkey
dc.relation.ispartofTurkish Journal of Electrical Engineering and Computer Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjectHybrid Taguchi-vortex search algorithm; Taguchi orthogonal arrays; vortex search algorithm; global optimization; engineering design problems with constraints
dc.titleA novel hybrid global optimization algorithm having training strategy: hybrid Taguchi-vortex search algorithm
dc.typeArticle

Dosyalar

Koleksiyon

WOS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
TR-Dizin İndeksli Yayınlar Koleksiyonu