Shape optimization of corrugated coatings under grazing incidence using a genetic algorithm

We report on the use of a genetic algorithm (GA) to design optimal shapes for a corrugated coating under near-grazing incidence. A full-wave electromagnetic solver based on the boundary integral formulation is employed to predict the performance of the coating shape. In our GA implementation, we encode each shape of the coating into a binary chromosome. A two-point crossover scheme involving three chromosomes and a geometrical filter are implemented to achieve efficient optimization. Standard magnetic radar absorbing material (MAGRAM) is used for the absorber coating. We present the optimized coating shapes depending on different polarizations. A physical interpretation for the optimized structure is discussed and the resulting shape is compared to conventional planar and triangular shaped designs. Next, we extend this problem from single to multiobjective optimization by using Pareto GA. The optimization results with two different objectives, viz. height (or weight) of the coating versus absorbing performance, are presented.