Pareto optimal design of absorbers using a parallel elitist nondominated sorting genetic algorithm and the finite element-boundary integral method

Microwave absorbing structures have many applications including the lining of anechoic chambers and the reduction of electromagnetic interference. Pareto optimization is an important tool in the design of absorbers, since most absorbers must be designed keeping both performance and economy in mind. In this paper, a new elitist strategy is implemented into the nondominated sorting genetic algorithm (NSGA) to effectively and efficiently design broadband high performance electromagnetic absorbers. The absorbers are analyzed using the finite element boundary integral method, and the optimization is accelerated with parallel processing. Numerical tests demonstrate that the elitist NSGA proposed in this paper converges faster that the standard NSGA and other classical techniques for a wide variety of absorber design problems. Finally, this efficient elitist NSGA is applied to design complex polygonal absorbers. Numerical results not only demonstrate the robustness of the design algorithm, but also reveal some important information and advantages related to absorber designs based on Pareto optimization.