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Comparison of the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, the salp swarm algorithm for real-world engineering applications

dc.contributor.authorGürses, Dildar
dc.contributor.authorBureerat, Sujin
dc.contributor.authorSait, Sadiq M.
dc.contributor.authorYıldız, Ali Rıza
dc.contributor.buuauthorGÜRSES, DİLDAR
dc.contributor.buuauthorYILDIZ, ALİ RIZA
dc.contributor.departmentBursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü.
dc.contributor.departmentBursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.
dc.contributor.researcherid JCN-8328-2023
dc.contributor.researcheridF-7426-2011
dc.date.accessioned2024-06-13T13:34:30Z
dc.date.available2024-06-13T13:34:30Z
dc.date.issued2021-01-01
dc.description.abstractThis paper focuses on a comparision of recent algorithms such as the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, and the salp swarm algorithm. The slime mold algorithm (SMA) is a recent optimization algorithm. In order to strengthen its exploitation and exploration abilities, in this paper, a new hybrid slime mold algorithm-simulated annealing algorithm (HSMA-SA) has been applied to structural engineering design problems. As a result of the rules and practices that have become mandatory for fuel emissions by international organizations and governments, there is increasing interest in the design of vehicles with minimized fuel emissions. Many scientific studies have been conducted on the use of metaheuristic methods for the optimum design of vehicle components, especially for reducing vehicle weight. With the inspiration obtained from the above-mentioned methods, the HSMA-SA has been studied to solve the shape optimization of a design case to prove how the HSMA-SA can be used to solve shape optimization problems. The HSMA-SA provides better results as an arithmetic optimization algorithm than the slime mold optimization algorithm, the marine predators algorithm, and the salp swarm algorithm.
dc.description.sponsorshipBursa Uludağ Üniversitesi, Bursa, Dhahran
dc.description.sponsorshipKaen University, Khon Kaen
dc.description.sponsorshipKing Fahd University of Petroleum Minerals
dc.description.sponsorshipPandit Deendayal Petroleum University, Gandhinagar
dc.identifier.doi10.1515/mt-2020-0076
dc.identifier.eissn2195-8572
dc.identifier.endpage452
dc.identifier.issn0025-5300
dc.identifier.issue5
dc.identifier.startpage448
dc.identifier.urihttps://doi.org/10.1515/mt-2020-0076
dc.identifier.urihttps://www.degruyter.com/document/doi/10.1515/mt-2020-0076/html
dc.identifier.urihttps://hdl.handle.net/11452/42174
dc.identifier.volume63
dc.identifier.wos000672581300009
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherWalter De Gruyter Gmbh
dc.relation.journalMaterials Testing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBiogeography-based optimization
dc.subjectDesign optimization
dc.subjectStructural optimization
dc.subjectHybrid approach
dc.subjectOptimum design
dc.subjectSearch
dc.subjectCrashworthiness
dc.subjectDesign optimization
dc.subjectArithmetic optimization algorithm
dc.subjectSlime mould optimization algorithm
dc.subjectMarine predators algorithm
dc.subjectSalp swarm algorithm
dc.subjectMaterials science
dc.titleComparison of the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, the salp swarm algorithm for real-world engineering applications
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublication1af1d254-5397-464d-b47b-7ddcbaff8643
relation.isAuthorOfPublication89fd2b17-cb52-4f92-938d-a741587a848d
relation.isAuthorOfPublication.latestForDiscovery1af1d254-5397-464d-b47b-7ddcbaff8643

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