Design of Circular and Concentric Circular Antenna Array Using an Improved Flower Pollination Algorithm

Abstract

Flower pollination algorithm (FPA) is a novel meta-heuristic algorithm inspired from pollination of flowers. It has been applied to various fields of research and proven its worth. But the algorithm suffers from certain limitations which confines its scope to different field of applications. In present work, a modified version of FPA namely an improved flower pollination algorithm (IFPA) has been proposed to improve exploration, enhance local search and to maintain good balance between intensification and diversification. Cauchy operator has been added instead of Levy flight for improving the explorative capability. Secondly, a modified probability switching has been used to balance exploration and exploitation. The last change considers the effect of current best for enhancing the local search phase. The results of IFPA are tested on twenty benchmark functions for different population sizes. The proposed approach is also tested on different dimension sizes of benchmark problems. The results of IFPA are then compared with differential evolution (DE), bat algorithm (BA), bat flower pollination algorithm (BFP) and flower pollination algorithm (FPA). Experimental results show that IFPA algorithm is better when compared to other algorithms. Further, statistical testing has been done to prove the significance of IFPA. IFPA is then tested on an important real-world application in the field of antenna design. Two different antenna synthesis design problem of circular antenna array (CAA) and concentric circular antenna array (CCAA) has been done using IFPA. Three cases of both arrays are analysed and then compared with different standard algorithms which shows the superiority of proposed approach in reducing the side lobe levels and first null beam width.