GitHub - alimirjalili/GWO: The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, three main steps of hunting, searching for prey, encircling prey, and attacking prey, are implemented to perform optimization. This is the source codes of the paper: S. Mirjalili, S. M. Mirjalili, A. Lewis, Grey Wolf Optimizer, Advances in Engineering Software, Volume 69, March 2014, Pages 46-61, ISSN 0965-9978, http://dx.doi.org/10.1016/j.advengsoft.2013.12.007. More information can be found in: http://www.alimirjalili.com/GWO.html

Name		Name	Last commit message	Last commit date
GWO.m		GWO.m
GWO.png		GWO.png
GWO_finalVersion.pdf		GWO_finalVersion.pdf
Get_Functions_details.m		Get_Functions_details.m
func_plot.m		func_plot.m
initialization.m		initialization.m
main.m		main.m

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The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, three main steps of hunting, searching for prey, encircling prey, and attacking prey, are implemented to perform optimiz…

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algorithms engineering engineering-optimisation genetic-algorithm grey-wolf-optimizer gwo heuristic-search-algorithms heuristics optimisation optimization optimization-algorithms particle-swarm-optimization seyedali-mirjalili

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