Advanced Cat Swarm Optimization for Sidelobe Reduction in Unequally Spaced Linear Antenna Arrays

This study introduces the Modified Cat Swarm Optimization (MCSO) algorithm, an advanced version of the traditional Cat Swarm Optimization (CSO) enhanced with Gaussian mutation. The Gaussian mutation facilitates a broader and more effective global search, mitigating issues of premature convergence and local optima that commonly affect the traditional CSO. The performance of MCSO was evaluated using standard benchmark mathematical problems, demonstrating superior accuracy and faster convergence compared to existing methods. Additionally, the MCSO was applied to the synthesis of linear aperiodic antenna arrays, optimizing element positions to minimize peak sidelobe levels. Results show that MCSO outperforms conventional algorithms in achieving lower sidelobe levels and faster convergence, highlighting its potential for applications in wireless communications and other engineering optimization problems.