Grey Wolf Optimizer

Modestus O. Okwu; Lagouge K. Tartibu

doi:10.1007/978-3-030-61111-8_5

Grey Wolf Optimizer

Modestus O. Okwu
, Lagouge K. Tartibu

Mechanical and Industrial Engineering Technology

University of Johannesburg

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

15 Citations (Scopus)

Abstract

GWO algorithm is a swarm or population-based meta-heuristic technique developed based on motivation from the hunting pattern of the Grey Wolves (GW). In this study, the model was implemented using MATLAB 2020. Thirty (30) search agents were considered and the maximum number of iterations was set to 1000. The best solution, best optimal value and objective function are presented in the study. GWO algorithm is considered useful for solving complex optimization problem.

Original language	English
Title of host publication	Studies in Computational Intelligence
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	43-52
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-030-61111-8_5
Publication status	Published - 2021

Publication series

Name	Studies in Computational Intelligence
Volume	927
ISSN (Print)	1860-949X
ISSN (Electronic)	1860-9503

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.1007/978-3-030-61111-8_5

Cite this

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M3 - Chapter

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Grey Wolf Optimizer

Abstract

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UN SDGs

ASJC Scopus subject areas

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