Evaluation of performance of adaptive and HybridABC (aABC) algorithm in solution of numerical optimization problems

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dc.contributor.author Kaya, Ebubekir
dc.date.accessioned 2022-12-14T07:35:04Z
dc.date.available 2022-12-14T07:35:04Z
dc.date.issued 2018-10-06
dc.identifier.uri http://hdl.handle.net/20.500.11787/7851
dc.description.abstract Artificial bee colony (ABC) algorithm is a heuristic optimization algorithm that models food search behavior of the honey bees. It is used to solve many real-world problems and has been successful. In the literature, it is seen that different modifications of ABC algorithm are proposed to obtain more effective results. In this study, adaptive and hybrid ABC (aABC) algorithm which is one of the modifications of ABC algorithm is used. Its performance is evaluated in solving numerical test functions. Unlike standard ABC algorithm, aABC algorithm uses arithmetic crossover and adaptive neighborhood radius in the solution generation mechanism. The applications are performed on 6 numerical test functions. The results are evaluated in terms of solution quality and convergence speed. In addition, Wilcoxon signed rank test is used to examine the significance of the results. The results show that aABC algorithm is more effective than ABC algorithm in solving numerical optimization problems. tr_TR
dc.language.iso eng tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Artificial bee colony tr_TR
dc.subject aABC algorithm tr_TR
dc.subject Numerical optimization problems tr_TR
dc.subject Optimization tr_TR
dc.title Evaluation of performance of adaptive and HybridABC (aABC) algorithm in solution of numerical optimization problems tr_TR
dc.type conferenceObject tr_TR
dc.relation.journal 2018 Akıllı Sistemlerde Yenilikler ve Uygulamaları Konferansı tr_TR
dc.contributor.department Nevşehir Hacı Bektaş Veli Üniversitesi/mühendislik-mimarlık fakültesi/bilgisayar mühendisliği bölümü/bilgisayar yazılımı anabilim dalı tr_TR
dc.contributor.authorID 108481 tr_TR


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