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Synthesis of Linear Antenna Arrays Using Enhanced Firefly Algorithm

机译：使用增强的萤火虫算法合成线性天线阵列

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摘要

Nature inspired algorithms are finding extensive applications in real-world applications. Firefly algorithm (FA) is one such swarm intelligent algorithm introduced in the recent past. This algorithm has proved its competitiveness over standard benchmark and real-world applications, but suffers from the problem of slow convergence speed. So, in order to overcome this problem, a modified FA approach called enhanced firefly algorithm (EFA) is proposed. The performance of the proposed EFA with respect to FA and other algorithms has been evaluated for eleven benchmark functions. The numerical results show that the novel method consistently provides better solution at a faster rate. Moreover, as a real-world application, EFA has been used for synthesis of linear antenna array for both equally and unequally spaced arrays. The results demonstrate that EFA provides reduced sidelobe level and faster convergence in comparison with algorithms like FA, biogeography-based optimization, cuckoo search, differential evolution, genetic algorithm, particle swarm optimization, tabu search and Taguchi method.
机译：受自然启发的算法正在实际应用中找到广泛的应用。萤火虫算法（FA）是最近引入的一种此类智能算法。该算法已经证明了其在标准基准测试和实际应用中的竞争力，但存在收敛速度慢的问题。因此，为了克服这个问题，提出了一种改进的FA方法，称为增强萤火虫算法（EFA）。相对于FA和其他算法，建议的EFA的性能已针对11种基准功能进行了评估。数值结果表明，该新方法始终以更快的速度提供更好的解决方案。此外，作为实际应用，EFA已被用于合成等距和不等距阵列的线性天线阵列。结果表明，与FA，基于生物地理的优化，布谷鸟搜索，差异进化，遗传算法，粒子群优化，禁忌搜索和Taguchi方法等算法相比，EFA降低了旁瓣水平，收敛速度更快。

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