Quasi-dynamic opposite learning enhanced Runge-Kutta optimizer for solving complex optimization problems

The Runge-Kutta Optimization (RUNGE) algorithm is a recently proposed metaphor-free metaheuristic optimizer borrowing practical mathematical foundations of the famous Runge-Kutta differential equation solver. Despite its relatively new emergence, this algorithm has several applications in various br...

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Vydáno v:	Evolutionary intelligence Ročník 17; číslo 4; s. 2899 - 2962
Hlavní autoři:	Turgut, Oguz Emrah, Turgut, Mert Sinan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2024 Springer Nature B.V
Témata:	Algorithms Applications of Mathematics Artificial Intelligence Bioinformatics Constraints Control Design engineering Differential equations Engineering Exploitation Genetic algorithms Heuristic Heuristic methods Hyperspaces Learning Mathematical and Computational Engineering Mechatronics Optimization Optimization algorithms Optimization techniques Ordinary differential equations Physics Research Paper Robotics Runge-Kutta method Searching Space exploration Statistical Physics and Dynamical Systems Benchmark functions Runge-Kutta optimization algorithm Dynamic-opposite learning Opposition-based learning Constrained optimization
ISSN:	1864-5909, 1864-5917
On-line přístup:	Získat plný text
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