Improved Fruit-Fly Optimization Algorithm and Its Applications in Antenna Arrays Synthesis

Synthesizing antenna arrays is one of the most influential optimization problems in the electromagnetics community. In this paper, an improved fruit-fly optimization algorithm (FOA) [entitled averager engine linear generation mechanism of candidate solution of FOA (AE-LGMS-FOA)] is proposed to be used in antenna array synthesis. This improvement includes adding a new search mechanism to enhance the efficiency of algorithm during high-dimensional problems. After investigating its performance through a variety of benchmark functions, the proposed method is applied to several linear and planar array problems in terms of sidelobe reduction, null control, and thinning. During the problems, some properties of the algorithm are analyzed and the associated results are compared with other state-of-the-art methods and popular algorithms. Furthermore, various boundary conditions are reformulated for the algorithm and examined during the planar array synthesis. Finally, the AE-LGMS-FOA is utilized in synthesizing a U-slot microstrip array antenna with ultrawideband characteristics to verify its versatility and robustness in real-world array antenna problems. The optimized structure has an impedance bandwidth of 3.38 GHz, which indicates 181.6% improvement over the original structure's bandwidth.

I. Introduction

Antenna arrays [1] are widely being used in wireless, radar, and mobile communication systems. Some of the most important applications of antenna arrays include beam forming [2], broadcasting [3], and other interesting applications, such as radio frequency identification [4] as well as heating applications [5]. The process of synthesizing arrays usually necessitates dealing with many additional construction parameters rather than a single-element geometry. As a result, it can be considered a high-dimensional optimization problem, which requires an advanced optimization technique.