This repository contains information and resources related to the Grey Wolf Optimization (GWO) algorithm, which is a nature-inspired optimization algorithm that mimics the social hierarchy and hunting mechanism of grey wolves.

The presentation slides for this algorithm were created for a university class and are included in the repository. You can find them in root directory of this repository. For better experience use powerpoint +2017.

The Grey Wolf Optimization algorithm is a metaheuristic algorithm inspired by the social behavior and hunting strategy of grey wolves. It was proposed by Dr. Seyedali Mirjalili. For detailed information about the algorithm, refer to the presentation slides or visit Dr. Mirjalili's website:

Dr. Seyedali Mirjalili's Website

To complement your understanding of the Grey Wolf Optimization algorithm, consider watching the following video that illustrates the hunting mechanism of grey wolves:

Grey Wolves Hunting Mechanism Video

• presentation_slides: Contains the presentation slides used for the university class.
• code: This directory can be used to store any code implementations or examples related to the GWO algorithm.

If you're interested in using the GWO algorithm for optimization problems, you can explore the code directory for implementation examples. Make sure to check the licensing information if you plan to use or modify any code provided in this repository.

• Dr. Seyedali Mirjalili for proposing the Grey Wolf Optimization algorithm.
• The video content is sourced from the video available at https://www.youtube.com/watch?v=VlZ5ddpqFbs&ab_channel=Piu.

Feel free to contribute, share, or provide feedback on this repository. Happy optimizing! ✋😉