Battle royale optimization algorithm

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dc.contributor.authorFarshi, Taymaz Rahkar
dc.date.accessioned2021-05-15T11:33:37Z
dc.date.available2021-05-15T11:33:37Z
dc.date.issued2021
dc.departmentMühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümüen_US
dc.descriptionRahkar-Farshi, Taymaz/0000-0003-4070-1058
dc.description.abstractRecently, several metaheuristic optimization approaches have been developed for solving many complex problems in various areas. Most of these optimization algorithms are inspired by nature or the social behavior of some animals. However, there is no optimization algorithm which has been inspired by a game. In this paper, a novel metaheuristic optimization algorithm, named BRO (battle royale optimization), is proposed. The proposed method is inspired by a genre of digital games knowns as "battle royale." BRO is a population-based algorithm in which each individual is represented by a soldier/player that would like to move toward the safest (best) place and ultimately survive. The proposed scheme has been compared with the well-known PSO algorithm and six recent proposed optimization algorithms on nineteen benchmark optimization functions. Moreover, to evaluate the performance of the proposed algorithm on real-world engineering problems, the inverse kinematics problem of the 6-DOF PUMA 560 robot arm is considered. The experimental results show that, according to both convergence and accuracy, the proposed algorithm is an efficient method and provides promising and competitive results.en_US
dc.identifier.doi10.1007/s00521-020-05004-4
dc.identifier.endpage1157en_US
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85085893913
dc.identifier.scopusqualityQ1
dc.identifier.startpage1139en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-020-05004-4
dc.identifier.urihttps://hdl.handle.net/20.500.12939/197
dc.identifier.volume33en_US
dc.identifier.wosWOS:000537363800005
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorFarshi, Taymaz Rahkar
dc.language.isoen
dc.publisherSpringer London Ltden_US
dc.relation.ispartofNeural Computing & Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBattle Royaleen_US
dc.subjectOptimizationen_US
dc.subjectSwarm Intelligenceen_US
dc.subjectMetaheuristicen_US
dc.titleBattle royale optimization algorithm
dc.typeArticle

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