Global Evolutionary Algorithms in the Design of Electromagnetic Band Gap Structures with Suppressed Surface Waves Propagation

The paper is focused on the automated design and optimization of electromagnetic band gap structures suppressing the propagation of surface waves. For the optimization, we use different global evolutionary algorithms like the genetic algorithm with the single-point crossover (GAs) and the multi-point (GAm) one, the differential evolution (DE) and particle swarm optimization (PSO). The algorithms are mutually compared in terms of convergence velocity and accuracy. The developed technique is universal (applicable for any unit cell geometry). The method is based on the dispersion diagram calculation in CST Microwave Studio (CST MWS) and optimization in Matlab. A design example of a mushroom structure with simultaneous electromagnetic band gap properties (EBG) and the artificial magnetic conductor ones (AMC) in the required frequency band is presented.