Publication: 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.author | Gürses, Dildar | |
dc.contributor.author | Bureerat, Sujin | |
dc.contributor.author | Sait, Sadiq M. | |
dc.contributor.author | Yıldız, Ali Rıza | |
dc.contributor.buuauthor | GÜRSES, DİLDAR | |
dc.contributor.buuauthor | YILDIZ, ALİ RIZA | |
dc.contributor.department | Mühendislik Fakültesi | |
dc.contributor.department | Makine Mühendisliği Bölümü | |
dc.contributor.researcherid | JCN-8328-2023 | |
dc.contributor.researcherid | F-7426-2011 | |
dc.date.accessioned | 2024-06-13T13:34:30Z | |
dc.date.available | 2024-06-13T13:34:30Z | |
dc.date.issued | 2021-01-01 | |
dc.description.abstract | This 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.sponsorship | Bursa Uludağ Üniversitesi, Bursa, Dhahran | |
dc.description.sponsorship | Kaen University, Khon Kaen | |
dc.description.sponsorship | King Fahd University of Petroleum Minerals | |
dc.description.sponsorship | Pandit Deendayal Petroleum University, Gandhinagar | |
dc.identifier.doi | 10.1515/mt-2020-0076 | |
dc.identifier.eissn | 2195-8572 | |
dc.identifier.endpage | 452 | |
dc.identifier.issn | 0025-5300 | |
dc.identifier.issue | 5 | |
dc.identifier.startpage | 448 | |
dc.identifier.uri | https://doi.org/10.1515/mt-2020-0076 | |
dc.identifier.uri | https://www.degruyter.com/document/doi/10.1515/mt-2020-0076/html | |
dc.identifier.uri | https://hdl.handle.net/11452/42174 | |
dc.identifier.volume | 63 | |
dc.identifier.wos | 000672581300009 | |
dc.indexed.wos | WOS.SCI | |
dc.language.iso | en | |
dc.publisher | Walter De Gruyter Gmbh | |
dc.relation.journal | Materials Testing | |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.subject | Biogeography-based optimization | |
dc.subject | Design optimization | |
dc.subject | Structural optimization | |
dc.subject | Hybrid approach | |
dc.subject | Optimum design | |
dc.subject | Search | |
dc.subject | Crashworthiness | |
dc.subject | Design optimization | |
dc.subject | Arithmetic optimization algorithm | |
dc.subject | Slime mould optimization algorithm | |
dc.subject | Marine predators algorithm | |
dc.subject | Salp swarm algorithm | |
dc.subject | Materials science | |
dc.title | 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.type | Article | |
dspace.entity.type | Publication | |
local.contributor.department | Mühendislik Fakültesi/Makine Mühendisliği Bölümü | |
local.contributor.department | Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü | |
relation.isAuthorOfPublication | 1af1d254-5397-464d-b47b-7ddcbaff8643 | |
relation.isAuthorOfPublication | 89fd2b17-cb52-4f92-938d-a741587a848d | |
relation.isAuthorOfPublication.latestForDiscovery | 1af1d254-5397-464d-b47b-7ddcbaff8643 |