Modified Grey Wolf Optimizer for Global Engineering Optimization
Joint Authors
Sohi, B. S.
Mittal, Nitin
Singh, Urvinder
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-05-04
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Information Technology and Computer Science
Abstract EN
Nature-inspired algorithms are becoming popular among researchers due to their simplicity and flexibility.
The nature-inspired metaheuristic algorithms are analysed in terms of their key features like their diversity and adaptation, exploration and exploitation, and attractions and diffusion mechanisms.
The success and challenges concerning these algorithms are based on their parameter tuning and parameter control.
A comparatively new algorithm motivated by the social hierarchy and hunting behavior of grey wolves is Grey Wolf Optimizer (GWO), which is a very successful algorithm for solving real mechanical and optical engineering problems.
In the original GWO, half of the iterations are devoted to exploration and the other half are dedicated to exploitation, overlooking the impact of right balance between these two to guarantee an accurate approximation of global optimum.
To overcome this shortcoming, a modified GWO (mGWO) is proposed, which focuses on proper balance between exploration and exploitation that leads to an optimal performance of the algorithm.
Simulations based on benchmark problems and WSN clustering problem demonstrate the effectiveness, efficiency, and stability of mGWO compared with the basic GWO and some well-known algorithms.
American Psychological Association (APA)
Mittal, Nitin& Singh, Urvinder& Sohi, B. S.. 2016. Modified Grey Wolf Optimizer for Global Engineering Optimization. Applied Computational Intelligence and Soft Computing،Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1094916
Modern Language Association (MLA)
Mittal, Nitin…[et al.]. Modified Grey Wolf Optimizer for Global Engineering Optimization. Applied Computational Intelligence and Soft Computing No. 2016 (2016), pp.1-16.
https://search.emarefa.net/detail/BIM-1094916
American Medical Association (AMA)
Mittal, Nitin& Singh, Urvinder& Sohi, B. S.. Modified Grey Wolf Optimizer for Global Engineering Optimization. Applied Computational Intelligence and Soft Computing. 2016. Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1094916
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1094916