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A new K-means grey wolf algorithm for engineering problems

Hardi M. Mohammed (Applied Computer Department, College of Medicals and Applied Sciences, Charmo University, Sulaimani, Iraq and Technical College of Informatics, Sulaimani Polytechnic University, Sulaimani, Iraq)
Zrar Kh. Abdul (Applied Computer Department, College of Medicals and Applied Sciences, Charmo University, Sulaimani, Iraq)
Tarik A. Rashid (Department of Computer Science and Engineering, School of Science and Engineering, University of Kurdistan Hewler, Erbil, Iraq)
Abeer Alsadoon (Information Technology Department, Asia Pacific International College (APIC), Sydney, Australia)
Nebojsa Bacanin (Faculty of Informatics and Computing, Singidunum University, Belgrade, Serbia)

World Journal of Engineering

ISSN: 1708-5284

Article publication date: 1 March 2021

Issue publication date: 29 July 2021

153

Abstract

Purpose

This paper aims at studying meta-heuristic algorithms. One of the common meta-heuristic optimization algorithms is called grey wolf optimization (GWO). The key aim is to enhance the limitations of the wolves’ searching process of attacking gray wolves.

Design/methodology/approach

The development of meta-heuristic algorithms has increased by researchers to use them extensively in the field of business, science and engineering. In this paper, the K-means clustering algorithm is used to enhance the performance of the original GWO; the new algorithm is called K-means clustering gray wolf optimization (KMGWO).

Findings

Results illustrate the efficiency of KMGWO against to the GWO. To evaluate the performance of the KMGWO, KMGWO applied to solve CEC2019 benchmark test functions.

Originality/value

Results prove that KMGWO is superior to GWO. KMGWO is also compared to cat swarm optimization (CSO), whale optimization algorithm-bat algorithm (WOA-BAT), WOA and GWO so KMGWO achieved the first rank in terms of performance. In addition, the KMGWO is used to solve a classical engineering problem and it is superior.

Keywords

Acknowledgements

The authors wish to thank Charmo University, Sulaimani Polytechnic University and the University of Kurdistan Hewler (UKH). This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.

Funding: this is not applicable.

Conflicts of interest/competing interests: there is no conflict of interest or competing interest is found.

Availability of data and material: data is available per request.

Code availability: data is available per request.

Citation

Mohammed, H.M., Abdul, Z.K., Rashid, T.A., Alsadoon, A. and Bacanin, N. (2021), "A new K-means grey wolf algorithm for engineering problems", World Journal of Engineering, Vol. 18 No. 4, pp. 630-638. https://doi.org/10.1108/WJE-10-2020-0527

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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