Many-Objective Cheetah Optimizer: A Novel Paradigm for Solving Complex Engineering Problems

Abstract Complex many-objective optimization problems (MaOPs) generate multiple challenges for obtaining convergence alongside diversity within extensive multi-dimensional solution areas. Optimization approaches currently face limitations when trying to balance exploration and exploitation especiall...

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Autors principals:	Pinank Patel, Divya Adalja, Nikunj Mashru, Pradeep Jangir, Arpita, Reena Jangid, G. Gulothungan, Ahmad O. Hourani, Kaznah Alshammari
Format:	Artigo
Idioma:	Inglês
Publicat:	Springer 2025-06-01
Col·lecció:	International Journal of Computational Intelligence Systems
Matèries:	High-dimensional objective spaces Exploration and exploitation Nature-inspired optimization Convergence and diversity Metaheuristic algorithms
Accés en línia:	https://doi.org/10.1007/s44196-025-00859-8
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