Hybrid Harmony Search Algorithm With Grey Wolf Optimizer and Modified Opposition-Based Learning

Hybrid Harmony Search Algorithm With Grey Wolf Optimizer and Modified Opposition-Based Learning

Most metaheuristic algorithms, including harmony search (HS), suffer from parameter selection. Many variants have been developed to cope with this problem and improve algorithm performance. In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem...

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Bibliographic Details
Main Authors: Alaa A. Alomoush, Abdulrahman A. Alsewari, Hammoudeh S. Alamri, Khalid Aloufi, Kamal Z. Zamli
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Computational intelligence
grey wolf optimizer
harmony search
hybrid algorithm
metaheuristic
optimization algorithm
Online Access:https://ieeexplore.ieee.org/document/8718294/

Internet

https://ieeexplore.ieee.org/document/8718294/

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