论文标题
使用进化编程和粒子群优化的杂种有效的天线优化
Efficient Antenna Optimization Using a Hybrid of Evolutionary Programing and Particle Swarm Optimization
论文作者
论文摘要
在本文中，我们介绍了一种进化编程（EP）和粒子群优化（PSO）算法的杂种，用于数值有效的天线阵列和元面孔的全局优化。混合EP-PSO算法采用一种进化优化方法，该方法将群体指示纳入标准的自适应EP算法中。作为示例，我们将此杂种技术应用于两个天线问题：非均匀间距（Aperiodic）线性阵列的侧杆级还原以及带有部分反射性元面的印刷天线的光束形状。给出了拟议的混合EP-PSO技术与eP-仅和仅PSO技术之间的详细比较，证明了该混合技术在复杂的天线设计问题中的效率。
In this paper, we present a hybrid of Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) algorithms for numerically efficient global optimization of antenna arrays and metasurfaces. The hybrid EP-PSO algorithm uses an evolutionary optimization approach that incorporates swarm directions in the standard self-adaptive EP algorithm. As examples, we have applied this hybrid technique to two antenna problems: the side-lobe-level reduction of a non-uniform spaced (aperiodic) linear array and the beam shaping of a printed antenna loaded with a partially reflective metasurface. Detailed comparisons between the proposed hybrid EP-PSO technique and EP-only and PSO-only techniques are given, demonstrating the efficiency of this hybrid technique in the complex antenna design problems.
