Mountain Gazelle Optimizer

Mountain Gazelle Optimizer: A new Nature-inspired Metaheuristic Algorithm for Global Optimization Problems

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Updated 6 Oct 2022

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The Mountain Gazelle Optimizer(MGO), a novel meta-heuristic algorithm inspired by the social life and hierarchy of wild mountain gazelles, is suggested in this paper. In this algorithm, gazelles' hierarchical and social life is formulated mathematically and used to develop an optimization algorithm. The MGO algorithm is evaluated and tested using Fifty-two standard benchmark functions and seven different engineering problems. It is compared with nine other powerful meta-heuristic algorithms to validate the result. The significant differences between the comparative algorithms are demonstrated using Wilcoxon's rank-sum and Friedman's tests. Numerous experiments have shown that the MGO performs better than the comparable algorithms on utmost benchmark functions. In addition, according to the tests performed, the MGO maintains its search capabilities and shows good performance even when increasing the dimensions of optimization problems.
Main paper:
Mountain Gazelle Optimizer: A new Nature-inspired Metaheuristic Algorithm for Global Optimization Problems Benyamin Abdollahzadeh,Farhad Soleimanian Gharehchopogh,Nima khodadadi, Seyedali Mirjalili, Advances in Engineering Software,2022
Email: benyamin.abdolahzade@gmail.com
Homepage:https://www.researchgate.net/profile/Benyamin-Abdollahzadeh

Cite As

benyamin abdollahzadeh (2023). Mountain Gazelle Optimizer (https://www.mathworks.com/matlabcentral/fileexchange/118680-mountain-gazelle-optimizer), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2021a
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Version Published Release Notes
1.0.1

Added some details

1.0.0