Background: Antennas serve a vital aspect in modern wireless communication. Designing antennas
with very high directivity is very important to solve the long-distance communication problem.
Though regularly excited and evenly spaced linear antenna arrays delivers good directivity but also leads
to problem related to higher side lobe. For diminishing the level of side lobe, the array can be constructed
either by amending the excitation amplitudes non-uniformly with all physical spaces of the antenna elements
keeping consistent or vice versa.
Methods: In this work, a novel mathematical objective function has been formulated. The objective function
has been solved using a recently developed evolutionary optimization technique, i.e., Binary cat
swarm optimization. So for better efficiency, the cat swarm optimization technique has been modified.
Results: The results have been compared with the popular algorithms like Genetic Algorithm (GA), Particle
Swarm Optimization (PSO), Cat Swarm Optimization (CSO) in terms of Side Lobe Level (SLL),
achieved fitness and execution time. The proposed algorithm achieves 0.5dB, 1.7 dB and 3dB smaller
SLL as compared to CSO, PSO and GA respectively. In addition to SLL, achieved fitness using BCSO is
in the range of 0.001 which is smallest among the compared algorithms.
Conclusion: It was found that the modified version namely binary cat swarm optimization algorithm outperform
other well-known evolutionary optimization algorithms.