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;Zich, Riccardo;
2020-01-01
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 | Dimensione | Formato | |
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