A Random Opposition-Based Learning Grey Wolf Optimizer

A Random Opposition-Based Learning Grey Wolf Optimizer

Grey wolf optimizer (GWO) algorithm is a swarm intelligence optimization technique that is recently developed to mimic the hunting behavior and leadership hierarchy of grey wolves in nature. It has been successfully applied to many real world applications. In the GWO algorithm, “C&#x2...

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Bibliographic Details
Main Authors: Wen Long, Jianjun Jiao, Ximing Liang, Shaohong Cai, Ming Xu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Grey wolf optimizer
random opposition learning
global optimization
engineering design optimization
exploration
exploitation
Online Access:https://ieeexplore.ieee.org/document/8795453/

Internet

https://ieeexplore.ieee.org/document/8795453/

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