Application of micro-genetic algorithm (MGA) to a class of electromagnetic analysis and synthesis problems

It is well known that the genetic algorithms (GAs) fall under a special category of optimization schemes that are robust stochastic search methods based on the principles of natural selection, and that they are particularly effective in searching for global maxima in a multidimensional and multi-modal functional domain. The GAs simultaneously process a population of points in the optimization space, and use stochastic operators to transition from one generation of points to the next, resulting in a decreased probability of them being trapped in local extremes. For electromagnetic problems, the GAs have found to a whole host of applications, for instance, the design of broadband antennas, spatial filter design, microwave absorber synthesis. We consider the problem of synthesizing broad-band microwave absorbers comprising frequency selective surfaces embedded in multilayered dielectric media in the frequency range from 19 to 36 GHz. We also consider the application of the MGA to the problem of extracting the equivalent circuit models for spiral inductors embedded in a multilayer structure.