Several Evolutionary Algorithms (EAs) are applied in the design and optimization of digital circuits, namely Genetic Algorithms (GAs), Memetic Algorithms (MAs) and swarm intelligence with Particle Swarm Optimization (PSO). GAs are optimization and search techniques based on the principles of genetics and natural selection. MAs are evolutionary algorithms that include a stage of individual optimization as part of its search strategy, being the individual optimization in the form of a local search. The combination of a global and a local search is a strategy used by many successful hybrid optimization approaches. PSO is a population-based search algorithm that starts with a population of random solutions called particles. In a PSO scheme each particle flies through the search space with a velocity that is adjusted dynamically according with its historical behavior. Therefore, the particles have a tendency to fly towards the best search area along the search process. In this line of thought, this paper presents the results for digital circuits design using the three above EAs.