Optimal design of planar terahertz Yagi-Uda antenna using adaptive chaos optimization algorithm

This paper presents a compact planar Yagi-Uda antenna for terahertz applications at 300 GHz for maximum gain and minimum return loss by optimizing the spaces between directors' elements beside their lengths and widths. The antenna parameters are optimized using the adaptive chaotic fruit fly optimization algorithm (CFOA) as a recent evolutionary-based algorithm. To show the convergence capability of the CFOA, the results are compared with those obtained by other evolutionary algorithms such as particle swarm optimization algorithm (PSO). The optimized antenna showed a return loss of -53 dB with high antenna gain of 14.2 dB. This enhancement is attributed to the efficient coupling between optimized array elements as well as reduced side and back-lobe levels. The comparison between different algorithms showed that the CFOA technique is superior to other evolutionary algorithms such as PSO by 39%.