Conceptual comparison of the ecogeography-based algorithm, equilibrium algorithm, marine predators algorithm and slime mold algorithm for optimal product design

dc.contributor.authorPatel, Vivek
dc.contributor.authorPholdee, Nantiwat
dc.contributor.authorSait, Sadiq M.
dc.contributor.authorBureerat, Sujin
dc.contributor.buuauthorYıldız, Betül Sultan
dc.contributor.buuauthorYıldız, Ali Rıza
dc.contributor.departmentUludağ Üniversitesi/Mühendislik Fakültesi/Makina Mühendisliği.
dc.contributor.orcid0000-0003-1790-6987
dc.contributor.orcid0000-0002-7493-2068
dc.contributor.researcheridAAL-9234-2020tr_TR
dc.contributor.researcheridF-7426-2011tr_TR
dc.contributor.scopusid57094682600tr_TR
dc.contributor.scopusid7102365439tr_TR
dc.date.accessioned2024-01-23T10:47:01Z
dc.date.available2024-01-23T10:47:01Z
dc.date.issued2021-07-01
dc.description.abstractVehicle component design is crucial for developing a vehicle prototype, as optimum parts can lead to cost reduction and performance enhancement of the vehicle system. The use of metaheuristics for vehicle component optimization has been commonplace due to several advantages: robustness and simplicity. This paper aims to demonstrate the shape design of a vehicle bracket by using a newly invented metaheuristic. The new optimizer is termed the ecogeography-based optimization algorithm (EBO). This is arguably the first vehicle design application of the new optimizer. The optimization problem is posed while EBO is implemented to solve the problem. It is found that the design results obtained from EBO are better when compared to other optimizers such as the equilibrium optimization algorithm, marine predators algorithm, slime mold algorithm.en_US
dc.description.sponsorshipKaen University, Khon Kaenen_US
dc.description.sponsorshipKing Fahd University of Petroleum Mineralsen_US
dc.description.sponsorshipPandit Deendayal Petroleum University, Gandhinagaren_US
dc.identifier.citationYıldız, B. S. vd. (2021). "Conceptual comparison of the ecogeography-based algorithm, equilibrium algorithm, marine predators algorithm and slime mold algorithm for optimal product design". Materialpruefung/Materials Testing, 63(4), 336-340.en_US
dc.identifier.endpage340tr_TR
dc.identifier.issn0025-5300
dc.identifier.issn2195-8572
dc.identifier.issue4tr_TR
dc.identifier.scopus2-s2.0-85106987273tr_TR
dc.identifier.startpage336tr_TR
dc.identifier.urihttps://doi.org/10.1515/mt-2020-0049
dc.identifier.urihttps://www.degruyter.com/document/doi/10.1515/mt-2020-0049/html
dc.identifier.urihttps://hdl.handle.net/11452/39268
dc.identifier.volume63tr_TR
dc.identifier.wos000645172500005tr_TR
dc.indexed.scopusScopustr_TR
dc.indexed.wosSCIEen_US
dc.language.isoenen_US
dc.publisherWalter De Gruyter GMBHen_US
dc.relation.bapBAPtr_TR
dc.relation.collaborationYurt içitr_TR
dc.relation.collaborationYurt dışıtr_TR
dc.relation.journalMaterialpruefung/Materials Testingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergitr_TR
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectStructural designen_US
dc.subjectEcogeography-based optimization algorithmen_US
dc.subjectEquilibrium optimization algorithmen_US
dc.subjectMarine predators algorithmen_US
dc.subjectSlime mould algorithmen_US
dc.subjectBiogeography-based optimizationen_US
dc.subjectSine-cosine algorithmen_US
dc.subjectStructural optimizationen_US
dc.subjectMulticomponent topologyen_US
dc.subjectSearch approachen_US
dc.subjectCrashworthinessen_US
dc.subjectCost reductionen_US
dc.subjectEcologyen_US
dc.subjectMoldsen_US
dc.subjectOptimizationen_US
dc.subjectVehiclesen_US
dc.subjectEquilibrium optimizationsen_US
dc.subjectOptimization algorithmsen_US
dc.subjectOptimizersen_US
dc.subjectSlime mouldsen_US
dc.subjectVehicle componentsen_US
dc.subjectProduct designen_US
dc.subject.scopusCutting Process; Chatter; Turningen_US
dc.subject.wosMaterials Science, Characterization & Testingen_US
dc.titleConceptual comparison of the ecogeography-based algorithm, equilibrium algorithm, marine predators algorithm and slime mold algorithm for optimal product designen_US
dc.typeArticleen_US
dc.wos.quartileQ2en_US

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