Publication:
A novel hybrid Harris hawks-simulated annealing algorithm and RBF-based metamodel for design optimization of highway guardrails

dc.contributor.authorKaen, Khon
dc.contributor.authorSait, Sadiq
dc.contributor.buuauthorYıldız, Ali Rıza
dc.contributor.buuauthorKurtuluş, Enes
dc.contributor.departmentMühendislik Fakültesi
dc.contributor.departmentMakine Mühendisliği
dc.contributor.orcid0000-0003-1790-6987
dc.contributor.scopusid7102365439
dc.contributor.scopusid56534007500
dc.date.accessioned2022-11-21T10:19:10Z
dc.date.available2022-11-21T10:19:10Z
dc.date.issued2020-02-25
dc.description.abstractIn this paper, a novel hybrid optimization algorithm is introduced by hybridizing a Harris hawks optimization algorithm(HHO) and simulated annealing for the purpose of accelerating its global convergence performance and optimizing structural design problems. This paper is the first research study in which the hybrid Harris hawks simulated annealing algorithm (HHOSA) is used for the optimization of design parameters for highway guardrail systems. The HHOSA is evaluated using the well-known benchmark problems such as the three-bar truss problem, cantilever beam problem, and welded beam problem. Finally, a guardrail system that has an H1 containment level as a case study is optimized to investigate the performance of the HHOSA. The guardrail systems are designed with different cross-sections and distances between the posts. TB11 and TB42 crash analyses are performed according to EN 1317 standards. Twenty-five different designs are evaluated considering weight, the guardrail working width, and the acceleration severity index (ASI). As a result of this research, the optimum design of a guardrail is obtained, which has a minimum weight and acceleration severity index value (ASI). The results show that the HHOSA is a highly effective approach for optimizing real-world design problems.
dc.description.sponsorshipKing Fahd University of Petroleum and Minerals
dc.identifier.citationKaen, K. vd. (2020). "A novel hybrid Harris hawks-simulated annealing algorithm and RBF-based metamodel for design optimization of highway guardrails". Materials Testing, 62(3), 51-260.
dc.identifier.endpage260
dc.identifier.issn0025-5300
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85081675861
dc.identifier.startpage251
dc.identifier.urihttps://doi.org/10.3139/120.111478
dc.identifier.urihttps://www.degruyter.com/document/doi/10.3139/120.111478/html
dc.identifier.urihttp://hdl.handle.net/11452/29514
dc.identifier.volume62
dc.identifier.wos000518458100003
dc.indexed.wosSCIE
dc.language.isoen
dc.publisherWalter de Gruyter
dc.relation.bapBAP
dc.relation.collaborationYurt içi
dc.relation.collaborationYurt dışı
dc.relation.journalMaterials Testing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectHarris hawks algorithm
dc.subjectSimulated annealing
dc.subjectCrash analysis
dc.subjectHybrid optimization algorithm
dc.subjectGuardrails
dc.subjectRoad safety barriers
dc.subjectParticle swarm optimization
dc.subjectOptimal machining parameter
dc.subjectStructual design
dc.subjectMultiobjective optimization
dc.subjectDifferential evolution
dc.subjectGenetic algorithm
dc.subjectGravitational search
dc.subjectGlobal optimization
dc.subjectImmune algorithm
dc.subjectOptimum design
dc.subjectHighway planning
dc.subjectMotor transportation
dc.subjectSimulated annealing
dc.subjectStructural design
dc.subjectGuard rails
dc.subjectAcceleration severity indices
dc.subjectCantilever beam problem
dc.subjectHybrid optimization algorithm
dc.subjectOptimization algorithms
dc.subjectStructural design problems
dc.subject.scopusCutting Process; Chatter; Turning
dc.subject.wosMaterials science, characterization & testing
dc.titleA novel hybrid Harris hawks-simulated annealing algorithm and RBF-based metamodel for design optimization of highway guardrails
dc.typeArticle
dc.wos.quartileQ3
dspace.entity.typePublication
local.contributor.departmentMühendislik Fakültesi/Makine Mühendisliği
local.indexed.atScopus
local.indexed.atWOS

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