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.

中文翻译：

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基于社交网络优化的波束扫描反射阵列天线设计程序

即使问题是高度非线性和多峰的，进化算法也可以成功地用于进行光束扫描无源反射阵列的有效设计。在本文中，社交网络优化（SNO）算法已用于评估光束扫描无源反射阵列（RA）的有效设计过程。为了充分利用SNO的优化功能，已对整个优化环境的各个部分进行了深入分析。通过与其他公认的进化算法进行比较，评估了SNO的性能和优化RA的束扫描能力。