The Harris hawks, grasshopper and multi-verse optimization algorithms for the selection of optimal machining parameters in manufacturing operations
dc.contributor.author | Sait, Sadiq M. | |
dc.contributor.author | Li, Xinyu | |
dc.contributor.buuauthor | Yıldız, Betül Sultan | |
dc.contributor.buuauthor | Yıldız, Ali Rıza | |
dc.contributor.department | Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü. | tr_TR |
dc.contributor.orcid | 0000-0003-1790-6987 | tr_TR |
dc.contributor.researcherid | AAL-9234-2020 | tr_TR |
dc.contributor.researcherid | F-7426-2011 | tr_TR |
dc.contributor.scopusid | 7102365439 | tr_TR |
dc.contributor.scopusid | 57094682600 | tr_TR |
dc.date.accessioned | 2022-11-29T09:59:16Z | |
dc.date.available | 2022-11-29T09:59:16Z | |
dc.date.issued | 2019-08 | |
dc.description.abstract | In this research, the Harris hawks optimization algorithm (HHO), the grasshopper optimization algorithm (GOA) and the multi-verse optimization algorithm (MVO) have been used in solving manufacturing optimization problems. This paper is the first research study for the optimization of processing parameters for manufacturing processes using the HHO, the GOA, and the MVO in the literature, and in particular, for grinding operations. A well-known grinding optimization problem is solved to prove how effective the HHO, the GOA and the MVO are in solving manufacturing problems and to demonstrate superiority over other algorithms. The results of the HHO, the GOA and the MVO are compared with other methods such as the genetic algorithm, the ant colony algorithm, the scatter search, the differential evolution algorithm, the particle swarm optimization algorithm, simulated annealing, the artificial bee colony, harmony search, improved differential evolution, the hybrid particle swarm algorithm, teaching learning-based optimization algorithms, the cuckoo search, and the fractal search algorithm. The results show that the HHO, the GOA, and the MVO are efficient optimization approaches for obtaining optimal manufacturing variables in manufacturing operations. | en_US |
dc.description.sponsorship | Huazhong University of Science and Technology | en_US |
dc.description.sponsorship | King Fahd University of Petroleum and Minerals | en_US |
dc.identifier.citation | Yıldız, B. S. vd. (2019). ''The Harris hawks, grasshopper and multi-verse optimization algorithms for the selection of optimal machining parameters in manufacturing operations''. Materials Testing, 61(8), 725-733. | en_US |
dc.identifier.endpage | 733 | tr_TR |
dc.identifier.issn | 0025-5300 | |
dc.identifier.issn | 2195-8572 | |
dc.identifier.issue | 8 | tr_TR |
dc.identifier.scopus | 2-s2.0-85072342939 | tr_TR |
dc.identifier.startpage | 725 | tr_TR |
dc.identifier.uri | https://doi.org/10.3139/120.111377 | |
dc.identifier.uri | https://www.degruyter.com/document/doi/10.1515/9783035624052-007/html | |
dc.identifier.uri | http://hdl.handle.net/11452/29621 | |
dc.identifier.volume | 61 | tr_TR |
dc.identifier.wos | 000478759900003 | tr_TR |
dc.indexed.scopus | Scopus | en_US |
dc.indexed.wos | SCIE | en_US |
dc.language.iso | en | en_US |
dc.publisher | Walter de Gruyter | en_US |
dc.relation.collaboration | Yurt dışı | tr_TR |
dc.relation.journal | Materials Testing | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | tr_TR |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Harris hawks optimization algorithm | en_US |
dc.subject | Grasshopper optimization algorithm | en_US |
dc.subject | Multi-verse optimization algorithm | en_US |
dc.subject | Manufacturing | en_US |
dc.subject | Grinding | en_US |
dc.subject | Design | en_US |
dc.subject | Structural design optimization | en_US |
dc.subject | Multiobjective optimization | en_US |
dc.subject | Water cycle algorithm | en_US |
dc.subject | Grinding process | en_US |
dc.subject | Genetic algorithm | en_US |
dc.subject | Gravitational search | en_US |
dc.subject | Immune algorithm | en_US |
dc.subject | Colony algorithm | en_US |
dc.subject | Topology desing | en_US |
dc.subject | Differential evolution | en_US |
dc.subject | Ant colony optimization | en_US |
dc.subject | Design | en_US |
dc.subject | Genetic algorithms | en_US |
dc.subject | Grinding (machining) | en_US |
dc.subject | Manufacture | en_US |
dc.subject | Particle swarm optimization (PSO) | en_US |
dc.subject | Simulated annealing | en_US |
dc.subject | Differential evolution algorithms | en_US |
dc.subject | Improved differential evolutions | en_US |
dc.subject | Manufacturing operations | en_US |
dc.subject | Optimal machining parameters | en_US |
dc.subject | Optimization algorithms | en_US |
dc.subject | Optimization of processing parameters | en_US |
dc.subject | Particle swarm optimization algorithm | en_US |
dc.subject | Teaching-learning-based optimizations | en_US |
dc.subject | Industrial research | en_US |
dc.subject.scopus | Cutting Process; Chatter; Turning | en_US |
dc.subject.wos | Materials science, sharacterization & testing | en_US |
dc.title | The Harris hawks, grasshopper and multi-verse optimization algorithms for the selection of optimal machining parameters in manufacturing operations | en_US |
dc.type | Article | |
dc.wos.quartile | Q4 | en_US |
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