The particle swarm optimization (PSO) algorithm has been the object of many studies and modifications for more than twentyfive years. Ranging from small refinements to the incorporation of sophisticated novel ideas, the majority of modifications proposed to this algorithm have been the result of a manual process in which developers try new designs based on their own knowledge and expertise. However, manually introducing changes is very time consuming and makes the systematic exploration of all the possible algorithm configurations a difficult process. In this paper, we propose to use automatic design to overcome the limitations of having to manually find performing PSO algorithms. We develop a flexible software framework for PSO, called PSO-X, which is specifically designed to integrate the use of automatic configuration tools into the process of generating PSO algorithms. Our framework embodies a large number of algorithm components developed over more than twentyfive years of research that have allowed PSO to deal with a large variety of problems, and uses irace, a state-of-the-art configuration tool, to automatize the task of selecting and configuring PSO algorithms starting from these components. We show that irace is capable of finding high performing instances of PSO algorithms never proposed before.