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dc.contributor.authorBoursianis, Achilles D
dc.contributor.authorPapadopoulou, Maria S
dc.contributor.authorSalucci, Marco
dc.contributor.authorPolo, Alessandro
dc.contributor.authorSarigiannidis, Panagiotis
dc.contributor.authorPsannis, Konstantinos
dc.contributor.authorMirjalili, Seyedali
dc.contributor.authorKoulouridis, Stavros
dc.contributor.authorGoudos, Sotirios K
dc.date.accessioned2021-09-15T04:03:30Z
dc.date.available2021-09-15T04:03:30Z
dc.date.issued2021
dc.identifier.issn2076-3417
dc.identifier.doi10.3390/app11188330
dc.identifier.urihttp://hdl.handle.net/10072/407992
dc.description.abstractSwarm 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.
dc.description.peerreviewedYes
dc.languageen
dc.publisherMDPI AG
dc.relation.ispartofpagefrom8330
dc.relation.ispartofissue18
dc.relation.ispartofjournalApplied Sciences
dc.relation.ispartofvolume11
dc.subject.fieldofresearchApplied computing
dc.subject.fieldofresearchArtificial intelligence
dc.subject.fieldofresearchDistributed computing and systems software
dc.subject.fieldofresearchcode4601
dc.subject.fieldofresearchcode4602
dc.subject.fieldofresearchcode4606
dc.titleEmerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationBoursianis, AD; Papadopoulou, MS; Salucci, M; Polo, A; Sarigiannidis, P; Psannis, K; Mirjalili, S; Koulouridis, S; Goudos, SK, Emerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers, Applied Sciences, 11 (18), pp. 8330
dcterms.licensehttps://creativecommons.org/licenses/by/4.0/
dc.date.updated2021-09-15T03:00:47Z
dc.description.versionVersion of Record (VoR)
gro.rights.copyright© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorMirjalili, Seyedali


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