Publication: A new hybrid artificial hummingbird-simulated annealing algorithm to solve constrained mechanical engineering problems
dc.contributor.author | Yıldız, Betül Sultan | |
dc.contributor.author | Mehta, Pranav | |
dc.contributor.author | Sait, Sadiq M. | |
dc.contributor.author | Panagant, Natee | |
dc.contributor.author | Kumar, Sumit | |
dc.contributor.author | Yıldız, Ali Rıza | |
dc.contributor.buuauthor | YILDIZ, BETÜL SULTAN | |
dc.contributor.buuauthor | YILDIZ, ALİ RIZA | |
dc.contributor.department | Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü. | |
dc.contributor.researcherid | AAL-9234-2020 | |
dc.contributor.researcherid | F-7426-2011 | |
dc.date.accessioned | 2024-10-14T13:11:44Z | |
dc.date.available | 2024-10-14T13:11:44Z | |
dc.date.issued | 2022-07-26 | |
dc.description.abstract | Nature-inspired algorithms known as metaheuristics have been significantly adopted by large-scale organizations and the engineering research domain due their several advantages over the classical optimization techniques. In the present article, a novel hybrid metaheuristic algorithm (HAHA-SA) based on the artificial hummingbird algorithm (AHA) and simulated annealing problem is proposed to improve the performance of the AHA. To check the performance of the HAHA-SA, it was applied to solve three constrained engineering design problems. For comparative analysis, the results of all considered cases are compared to the well-known optimizers. The statistical results demonstrate the dominance of the HAHA-SA in solving complex multi-constrained design optimization problems efficiently. Overall study shows the robustness of the adopted algorithm and develops future opportunities to optimize critical engineering problems using the HAHA-SA. | |
dc.identifier.doi | 10.1515/mt-2022-0123 | |
dc.identifier.endpage | 1050 | |
dc.identifier.issn | 0025-5300 | |
dc.identifier.issue | 7 | |
dc.identifier.startpage | 1043 | |
dc.identifier.uri | https://doi.org/10.1515/mt-2022-0123 | |
dc.identifier.uri | https://www.degruyter.com/document/doi/10.1515/mt-2022-0123/html | |
dc.identifier.uri | https://hdl.handle.net/11452/46390 | |
dc.identifier.volume | 64 | |
dc.identifier.wos | 000821392200012 | |
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 | Search algorithm | |
dc.subject | Truss structures | |
dc.subject | Optimization algorithm | |
dc.subject | Design optimization | |
dc.subject | Crashworthiness | |
dc.subject | Artificial hummingbird algorithm | |
dc.subject | Planetary gear train | |
dc.subject | Simulated annealing | |
dc.subject | Ten bar truss problem | |
dc.subject | Vehicle crash problem | |
dc.subject | Materials science | |
dc.title | A new hybrid artificial hummingbird-simulated annealing algorithm to solve constrained mechanical engineering problems | |
dc.type | Article | |
dspace.entity.type | Publication | |
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relation.isAuthorOfPublication | 89fd2b17-cb52-4f92-938d-a741587a848d | |
relation.isAuthorOfPublication.latestForDiscovery | e544f464-5e4a-4fb5-a77a-957577c981c6 |