Evolutionary algorithms can be successfully exploited for carrying on an effective design of beam-scanning passive reflectarrays, even if the problem is highly non-linear and multimodal. In this article, the Social Network Optimization (SNO) algorithm has been used for assessing an effective design procedure of a beam-scanning passive reflectarray (RA). For exploiting at most the optimization capabilities of SNO, the entire optimization environment has been deeply analyzed in all its parts. The performance of SNO and the beam-scanning capabilities of the optimized RA have been assessed through the comparison with other well established Evolutionary Algorithms.

Social Network Optimization Based Procedure for Beam-Scanning Reflectarray Antenna Design / Niccolai, Alessandro; Beccaria, Michele; Zich, Riccardo E.; Massaccesi, Andrea; Pirinoli, Paola. - In: IEEE OPEN JOURNAL OF ANTENNAS AND PROPAGATION. - ISSN 2637-6431. - 1:(2020), pp. 500-512. [10.1109/OJAP.2020.3022935]

Social Network Optimization Based Procedure for Beam-Scanning Reflectarray Antenna Design

Beccaria, Michele;Massaccesi, Andrea;Pirinoli, Paola
2020

Abstract

Evolutionary algorithms can be successfully exploited for carrying on an effective design of beam-scanning passive reflectarrays, even if the problem is highly non-linear and multimodal. In this article, the Social Network Optimization (SNO) algorithm has been used for assessing an effective design procedure of a beam-scanning passive reflectarray (RA). For exploiting at most the optimization capabilities of SNO, the entire optimization environment has been deeply analyzed in all its parts. The performance of SNO and the beam-scanning capabilities of the optimized RA have been assessed through the comparison with other well established Evolutionary Algorithms.
File in questo prodotto:
File Dimensione Formato  
Beccaria-Social.pdf

accesso aperto

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Creative commons
Dimensione 2.2 MB
Formato Adobe PDF
2.2 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2866672