Grey Wolf Optimizer (GWO)

GWO is a novel meta-heuristic algorithm for global optimization
Updated 22 May 2018

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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 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,
More information can be found in:
You can find the Grey Wolf optimizer Toolbox here:
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Cite As

Seyedali Mirjalili (2024). Grey Wolf Optimizer (GWO) (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2011b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

Links added:
A link has been added to the description

This submission is now available as a Toolbox file in R2014b.

Typo fixed

The paper has been included in the submission.

A link to the GWO toolbox was added.

An issue in boundary checking was resolved and the source filed have been updated.