Advances in Mountain Gazelle Optimizer: A Comprehensive Study on its Classification and Applications

Abstract The Mountain Gazelle Optimizer (MGO) is a newly emerging nature-inspired metaheuristic algorithm based on mountain gazelles' regionally and adaptively directed behavior. It is intended to solve complex optimization problems with an effective balance of exploration and exploitation. The MGO...

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Hlavní autoři:	Ferzat Anka, Farhad Soleimanian Gharehchopogh, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Springer 2025-10-01
Edice:	International Journal of Computational Intelligence Systems
Témata:	Mountain gazelle optimizer Metaheuristic algorithm Classification Hybrid methods Improved performance
On-line přístup:	https://doi.org/10.1007/s44196-025-00968-4
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