TY - JOUR
T1 - Emerging swarm intelligence algorithms and their applications in antenna design
T2 - The gwo, woa, and ssa optimizers
AU - Boursianis, Achilles D.
AU - Papadopoulou, Maria S.
AU - Salucci, Marco
AU - Polo, Alessandro
AU - Sarigiannidis, Panagiotis
AU - Psannis, Konstantinos
AU - Mirjalili, Seyedali
AU - Koulouridis, Stavros
AU - Goudos, Sotirios K.
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/9
Y1 - 2021/9
N2 - 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.
AB - 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.
KW - Antenna design
KW - Aperture-coupled antenna
KW - Grey wolf optimizer
KW - Meta-heuristics
KW - Nature-inspired algorithms
KW - Optimization technique
KW - Salp swarm algorithm
KW - Swarm intelligence
KW - Whale optimization algorithm
UR - http://www.scopus.com/inward/record.url?scp=85114704245&partnerID=8YFLogxK
U2 - 10.3390/app11188330
DO - 10.3390/app11188330
M3 - Article
AN - SCOPUS:85114704245
VL - 11
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
SN - 2076-3417
IS - 18
M1 - 8330
ER -