The advantages of using structured populations in Evolutionary Algorithms (EAs) and other metaheuristicas are well known today, not only for parallelization purposes, but also for enhancing the performance of the algorithm with respect to the equivalent algorithm with panmictic population, even for sequential executions. The use of an appropriate population structure will allow us to create a higher efficiency and efficacy algorithm once structured, both numerically and in real time (e.g. parallelism). The articles composing this special issue represent excellent novel contributions in this direction. We collected six high-quality papers out of the 43 received ones. These finally selected papers deal with different aspects related to the topic of this special issue, such as theoretical studies, identification of current challenges in the field, novel population structure designs, and empirical validation on highly complex problems.