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Grey Wolf Optimizer

What is this algorithm?

Single-objective optimization

Single-objective optimization

The Grey Wolf Optimizer (GWO) 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. 

Single-objective optimization

Single-objective optimization

Single-objective optimization

GWO has been designed to solve single-objective optimization problems. This algorithm has been implemented in a wide range of programming languages. You can download the source code at the bottom of this page. 

Download gwo matlab code

Multi-objective optimization

Single-objective optimization

If you are interested in solving a multi-objective problem using GWO, you have to use this code. 

Download MOGWO Matlab code

Matlab GWO toolbox

A user-friendly interface to run GWO algorithm with minimum coding. 

Download GWO Matlab Toolbox

Improved GWO

Improved GWO

One of the best improvements of GWO called I-GWO (Credits to Dr.  Mohammad H. Nadimi-Shahraki).

Download I-GWO Matlab code

GWO in Different Programming Languages

Java implementation of GWO

Tutorials on GWO

Let's learn the inspiration

Watch this video to learn about the inspirations for the GWO algorithm. 

Let's learn the mathematical models for GWO

 Watch this video to learn how and what I have designed the mathematical equatiosn for the GWO algorithm.  

Let's see how mathematical equations of GWO work

Watch this video to learn the role of the main controlling parameters in this algorithm.  

For More Videos

Please enrol to my Udemy course

Play with GWO parameters in one dimension

Play with GWO parameters in two dimensions

Play with alpha, beta, delta, and omega in GWO

Read More About GWO

Download PDF

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