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Grey Wolf Optimizer for Training Multi-Layer Perceptrons

version 1.2 (6.36 KB) by Seyedali Mirjalili
The submission employs the recently proposed Grey Wolf Optimizer for training Multi-Layer Perceptron


Updated 22 May 2018

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Grey Wolf Optimizer (GWO) is employed as a trainer for Multi-Layer Perceptron (MLP). The current source codes are the demonstration of the GWO trainer for solving the "Iris" classification problem.
This is the demonstration source codes of the paper:
S. Mirjalili, How effective is the GreyWolf optimizer in training multi-layer perceptrons, Applied Intelligence, In press, 2015, DOI:

More information can be found in my personal web page:

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Cite As

Seyedali Mirjalili (2021). Grey Wolf Optimizer for Training Multi-Layer Perceptrons (, MATLAB Central File Exchange. Retrieved .

Comments and Ratings (6)

Laurence Maregedze

Wonderful information


Dear Dr.Seyedali Mirjalili,
Firstly, I would like to thank you for a very nice contribution and I doubt that the exact number of dimension for the cancer data set should be 210(it is programmed as 209).I was trying to modify it to 210 but can't resolve the error, Have you checked that or any reason for taking 209?
Thank you in Advance!

Ali sameer

can you please help me to convert your ANN Code from Classification Learner to advised machine learning . I need it for regression and forecasting purposes.

sujan ghimire

CAn it be used for regression poblem?

John Albert

Can GWO be used for regression problem ? I have a dataset of 7 input variable with 6 input and 1 output?


If I change runno to any number like 3 the error appear
Attempted to access Best-pos(2,1) index out of bounds because size(Best-pos)=[1,46]

MATLAB Release Compatibility
Created with R2011b
Compatible with any release
Platform Compatibility
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