Linear antenna array optimization using flower pollination algorithm

• Published in: SpringerPlus Vol. 5; no. 1; p. 306
• Main Authors: Saxena, Prerna, Kothari, Ashwin
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 10.03.2016; Springer Nature B.V
• Subjects: Algorithms; Engineering; Flowers; Humanities and Social Sciences; multidisciplinary; Pollination; Science; Science (multidisciplinary); Side lobe level; Null placement; Evolutionary algorithms; Antenna array optimization; Linear antenna array; Flower pollination algorithm
• ISSN: 2193-1801; 2193-1801
• DOI: 10.1186/s40064-016-1961-7

Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pattern with minimum side lobe level along with placement of deep nulls in desired directions. Various design examples are presented that illustrate the use of FPA for linear antenna array optimization, and subsequently the results are validated by benchmarking along with results obtained using other state-of-the-art, nature-inspired evolutionary algorithms such as particle swarm optimization, ant colony optimization and cat swarm optimization. The results suggest that in most cases, FPA outperforms the other evolutionary algorithms and at times it yields a similar performance.