Hybrid Optimization Algorithm for Design and Characterization of Microstrip Planar Antenna

ABSTRACT The evolution of wireless communication systems has driven the demand for efficient, compact, and versatile antenna designs. Among the various types of antennas, microstrip planar antennas have gained significant attention due to their low‐profile structure, compatibility with modern electronic circuits, and ease of fabrication. Designing a microstrip planar antenna using optimization techniques involves finding the optimal parameters that result in the best performance for specific design criteria, which significantly improves the performance of the antenna while also minimizing costs and space requirements. Accordingly, this paper proposes a novel optimal design for a microstrip planar antenna. This study focused on designing an optimal microstrip planar antenna by a new optimization algorithm termed rhinopithecus swarm assisted hippopotamus optimization (RAHO) by carefully considering key parameters and that significantly influence the antenna's performance. The analysis proves the performance of the proposed antenna design with maximization of antenna gain with 6.41% enhancement than the RSOA algorithm.