Meta-Heuristics Optimization Algorithms for Solving Antenna Synthesis Problem

Sk Thaherbasha, Giriveni Shiva, Kandakatla Karthik, Vadala Prathyusha, Sana
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Abstract

This paper aims to develop meta-heuristics optimization algorithms for solving real-world engineering problems. One of the real-world engineering problem that we are going to solve is the antenna synthesis problem. The antenna synthesis problem involves designing an antenna that meets specific performance criteria. Meta-heuristics optimization algorithms are a group of algorithms particularly suited for solving optimization problems, such as the antenna synthesis problem. One that type of algorithm is the particle swarm optimization (PSO) algorithm, which is more efficient in optimizing various antennas, including linear, planar, and conformal antennas. In summary, meta-heuristics optimization algorithms, such as the PSO algorithm, provide an effective means for solving the antenna synthesis problem by searching the solution space for optimal solutions. These algorithms can be applied to various antennas and can optimize parameters, such as geometry and material properties, to achieve specific performance criteria.
求解天线综合问题的元启发式优化算法
本文旨在开发用于解决实际工程问题的元启发式优化算法。我们要解决的一个现实工程问题是天线合成问题。天线综合问题涉及到设计满足特定性能标准的天线。元启发式优化算法是一组特别适合于解决优化问题的算法,例如天线综合问题。其中一种算法是粒子群优化(PSO)算法,该算法在优化各种天线(包括线性、平面和共形天线)方面效率更高。综上所述,粒子群算法等元启发式优化算法通过在解空间中搜索最优解,为解决天线综合问题提供了有效手段。这些算法可以应用于各种天线,并可以优化参数,如几何形状和材料特性,以达到特定的性能标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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