One of the challenges for the future cyber-physical systems is the exploration of large design spaces. Genetic algorithms (GAs), which embody a simplified computational model of the mutation and selection mechanisms of natural evolution, are known to be effective for design optimization. However, the traditional formulations are limited to choosing values for a predetermined set of parameters within a given fixed architecture.