The Grey Wolf Optimizer and Its Applications in Electromagnetics

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

3 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Article number8889465
Pages (from-to)2186-2197
Journal / PublicationIEEE Transactions on Antennas and Propagation
Volume68
Issue number3
Online published31 Oct 2019
Publication statusPublished - Mar 2020

Abstract

The grey wolf optimizer (GWO) is a newly developed swarm intelligence-based optimization technique that mimics the social hierarchy and group hunting behavior of grey wolves in nature. Here, a detailed introduction of the GWO algorithm is given, after which, three sets of examples are investigated: first, numerical experiments on four benchmark functions are conducted; second, the GWO is applied to the synthesis of linear arrays with the aim of reducing the peak sidelobe level under various constraints; and finally, the performance of the GWO is further verified on the optimization design of two representative antennas, namely, a dual-band E-shaped patch antenna and a wideband magneto-electric dipole antenna. The results show that the GWO is capable of outperforming or providing very competitive results compared with some well-known metaheuristics such as the genetic algorithm, particle swarm optimization, and differential evolution. Thus, it may serve as a promising candidate for handling electromagnetic problems.

Research Area(s)

  • Antenna arrays, aperiodic arrays, genetic algorithm (GA), grey Wolf optimizer (GWO), magneto-electric (ME) dipole antenna, microstrip patch antenna, particle swarm optimization (PSO)