A new neural network-assisted hybrid chaotic hiking optimization algorithm for optimal design of engineering components

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dc.authorid0000-0002-1361-7363
dc.contributor.authorOzcan, Ahmet Remzi
dc.contributor.authorMehta, Pranav
dc.contributor.authorSait, Sadiq M.
dc.contributor.authorGurses, Dildar
dc.contributor.authorYildiz, Ali Riza
dc.date.accessioned2026-02-08T15:15:46Z
dc.date.available2026-02-08T15:15:46Z
dc.date.issued2025
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractIn the era of artificial intelligence (AI), optimization and parametric studies of engineering and structural systems have become feasible tasks. AI and ML (machine learning) offer advantages over classical optimization techniques, which often face challenges such as slower convergence, difficulty handling multiobjective functions, and high computational time. Modern AI and ML techniques may not effectively address all critical design engineering problems despite these advancements. Nature-inspired algorithms based on physical phenomena in nature, human behavior, swarm intelligence, and evolutionary principles present a viable alternative for multidisciplinary design optimization challenges. This article explores the optimization of various engineering problems using a newly developed modified hiking optimization algorithm (HOA). The algorithm is inspired by human hiking techniques, such as hill climbing and hiker speed. The advantages of the modified HOA are compared with those of several famous algorithms from the literature, demonstrating superior results in terms of statistical measures.
dc.identifier.doi10.1515/mt-2024-0519
dc.identifier.endpage1078
dc.identifier.issn0025-5300
dc.identifier.issn2195-8572
dc.identifier.issue6
dc.identifier.scopus2-s2.0-105002678537
dc.identifier.scopusqualityQ2
dc.identifier.startpage1069
dc.identifier.urihttps://doi.org/10.1515/mt-2024-0519
dc.identifier.urihttps://hdl.handle.net/20.500.12885/5963
dc.identifier.volume67
dc.identifier.wosWOS:001463525000001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherWalter De Gruyter Gmbh
dc.relation.ispartofMaterials Testing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzWOS_KA_20260207
dc.subjecthiking optimization algorithm
dc.subjectartificial neural network
dc.subjectchaotic maps
dc.subjectreal-world applications
dc.subjectengineering design
dc.titleA new neural network-assisted hybrid chaotic hiking optimization algorithm for optimal design of engineering components
dc.typeArticle

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