Hybrid optimization model for design and optimization of microstrip patch antenna.

The antenna design for a specified resonant frequency necessitates the computation of optimal values of different sizes. This is a harder task for microstrip patch antenna (MPA) since there is no precise numerical formula that leads to accurate solutions for designing these antennas. Presently, bio-inspired approaches are widely deployed in numerous antenna designs and it has revealed an immense assurance in handling the rising necessities of antenna engineering for overall cost, reduced size, and enhanced performances. This work aims to introduce an optimal MPA design, where the antenna elements like patch length, patch height, substrate width, and substrate length are optimally tuned by a new hybrid optimization model. For this, a new hybridized model known as shark smell integrated EHO is proposed. Eventually, the primacy of the suggested model is scrutinized via varied assessments.