A novel hybrid RUN-ABC optimization algorithm

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dc.authorid0000-0002-3645-3445
dc.contributor.authorYelmenoğlu, Elif Denizen_US
dc.contributor.editorPajenado, Rex S.en_US
dc.contributor.editorDilli, Şirinen_US
dc.date.accessioned2026-02-19T08:27:16Z
dc.date.available2026-02-19T08:27:16Z
dc.date.issued2025-10-08
dc.departmentIşık Üniversitesi, İktisadi, İdari ve Sosyal Bilimler Fakültesi, Enformasyon Teknolojileri Bölümüen_US
dc.departmentIşık University, Faculty of Economics, Administrative and Social Sciences, Department of Information Technologiesen_US
dc.description.abstractIn recent years, with the development of technology, complex and high-dimensional problems have increased. The use of metaheuristic optimization algorithms in solving these complex problems has become an important research area. In this study, a new hybrid RUN-ABC optimization algorithm was developed by combining the RUN (Runge Kutta Optimization) algorithm and the ABC (Artificial Bee Colony) algorithm. By taking into account the powerful exploration capabilities of the ABC algorithm and the efficient exploitation capabilities of the RUN algorithm, the aim was to search for the best solution in a more balanced manner in the search space. Experiments were conducted on five different benchmark functions to evaluate the performance of the hybrid RUN-ABC method. In these experiments, the developed hybrid method ABC and RUN algorithms were compared based on the average best value, standard deviation, and convergence rate. Furthermore, the Wilcoxon signed-rank test (signrank) was applied to measure the performance between the algorithms. The results showed that the developed hybrid RUN-ABC algorithm outperformed both the RUN and ABC algorithms in most cases. The developed method demonstrated impressive performance in terms of achieving a global minimum and the stability of its results. This study demonstrates that the developed hybrid RUN-ABC method can be a powerful alternative and provides a basis for its future use in solving various complex problems.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationYelmenoğlu, E. D. (2025). A novel hybrid RUN-ABC optimization algorithm. Paper presented at the 17th International Istanbul Scientific Research Congress, 1001-1001. doi:https://doi.org/10.30546/19023.978-9952-8596-8-3.2025.0031en_US
dc.identifier.endpage1001
dc.identifier.isbn9789952859683
dc.identifier.startpage1001
dc.identifier.urihttps://hdl.handle.net/11729/7027
dc.identifier.urihttps://doi.org/10.30546/19023.978-9952-8596-8-3.2025.0031
dc.institutionauthorYelmenoğlu, Elif Denizen_US
dc.institutionauthorid0000-0002-3645-3445
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherBZT Turan Publishing Houseen_US
dc.relation.ispartof17th International Istanbul Scientific Research Congressen_US
dc.relation.publicationcategoryKonferans Öğesi - Ulusal - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectMetaheuristic optimizationen_US
dc.subjectOptimization algorithmsen_US
dc.subjectHybrid algorithmsen_US
dc.titleA novel hybrid RUN-ABC optimization algorithmen_US
dc.typeConference Objecten_US
dspace.entity.typePublicationen_US

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