Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1534
Title: Emerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers
Authors: Boursianis, Achilles D.
Papadopoulou, Maria S.
Salucci, Marco
Polo, Alessandro
Sarigiannidis, Panagiotis
Psannis, Kostas E.
Mirjalili, Seyedali
Koulouridis, Stavros
Goudos, Sotirios K.
Type: Article
Subjects: FRASCATI::Engineering and technology
FRASCATI::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
Keywords: antenna design
aperture-coupled antenna
meta-heuristics
nature-inspired algorithms
optimization technique
swarm intelligence
grey wolf optimizer
whale optimization algorithm
salp swarm algorithm
Issue Date: 2021
Source: Applied Sciences
Volume: 11
Issue: 18
First Page: 8330
Abstract: Swarm Intelligence (SI) Algorithms imitate the collective behavior of various swarms or groups in nature. In this work, three representative examples of SI algorithms have been selected and thoroughly described, namely the Grey Wolf Optimizer (GWO), the Whale Optimization Algorithm (WOA), and the Salp Swarm Algorithm (SSA). Firstly, the selected SI algorithms are reviewed in the literature, specifically for optimization problems in antenna design. Secondly, a comparative study is performed against widely known test functions. Thirdly, such SI algorithms are applied to the synthesis of linear antenna arrays for optimizing the peak sidelobe level (pSLL). Numerical tests show that the WOA outperforms the GWO and the SSA algorithms, as well as the well-known Particle Swarm Optimizer (PSO), in terms of average ranking. Finally, the WOA is exploited for solving a more computational complex problem concerned with the synthesis of an dual-band aperture-coupled E-shaped antenna operating in the 5G frequency bands
URI: https://doi.org/10.3390/app11188330
https://ruomo.lib.uom.gr/handle/7000/1534
ISSN: 2076-3417
Other Identifiers: 10.3390/app11188330
Appears in Collections:Department of Applied Informatics

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