Optimizing Linear Antenna Arrays with The Chaotic Gold Rush Optimizer

In this paper, we introduce the gold rush optimization algorithm to an antenna array for the first time. We have enhanced the gold rush optimization algorithm by introducing logistic-tent mapping, resulting in the Chaotic Gold Rush Optimizer (CGRO). This innovative approach effectively overcomes the limitations of premature convergence to local optima, facilitating the design of linear antenna arrays with improved directivity and reduced side lobe levels (SLL). The proposed algorithm is utilized for the synthesis of sparse linear array antennas. Findings demonstrate its ability to further reduce peak sidelobe levels and enhance the functionality of linear sparse arrays. The high adaptability and efficiency of CGRO in optimizing complex antenna designs provide a promising tool for achieving optimal antenna configurations in wireless communication systems.