Synthesis of Linear Antenna Arrays Using Enhanced Firefly Algorithm

• Published in: Arabian journal for science and engineering (2011) Vol. 44; no. 3; pp. 1961 - 1976
• Main Authors: Singh, Urvinder, Salgotra, Rohit
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 11.03.2019; Springer Nature B.V
• Subjects: Algorithms; Antenna arrays; Antennas; Benchmarks; Convergence; Engineering; Evolutionary algorithms; Evolutionary computation; Genetic algorithms; Heuristic methods; Humanities and Social Sciences; multidisciplinary; Particle swarm optimization; Research Article - Electrical Engineering; Science; Search algorithms; Sidelobe reduction; Sidelobes; Synthesis; Tabu search; Taguchi methods; Side lobe level; Swarm intelligence; Enhanced firefly algorithm; Linear antenna arrays; Firefly algorithm
• ISSN: 2193-567X; 1319-8025; 2191-4281
• DOI: 10.1007/s13369-018-3214-2

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.