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Welcome to part 2 of the two-part special issue on parallel and distributed Evolutionary Algorithms (EAs). This special issue targets a wide set of researchers ranging from specialists in parallel computing for evolutionary computation to researchers interested in using the methodology for solving difficult practical problems. As already pointed out in the editorial of part 1 [1], despite the long history of parallel and distributed approaches in EAs, still a lot of motivations exist for a new presentation of the state of the art in the field, ranging from the fact that engineers and scientists wish to tackle problems of ever increasing complexity with a consequent increase in computational costs, to the growing availability of relativelty cheap parallel/distributed hardware and the emergence of standard software environments (for instance MPI or the numerous existing frameworks for exploiting the computational power of computer GRIDs). Another remarkable emerging trend, well represented by the papers that appear in the present issue, consists in the use of graphical processing units (GPUs), which are inexpensive, can be easily harnessed, and provide excellent speedup in the case of evolutionary algorithms. The fact that parallel and distributed EAs is still a very active research field is also testified by the unusually high number (twenty-five) of high-quality submissions that we received in response to our call for papers, ten of which were accepted for publication after extensive review. Five of these papers appeared in part 1 of this special issue [1], while the remaining five appear here. All of the papers were subject to the same review and editorial standards as any regular paper in this journal.

Guest editorial: special issue on parallel and distributed evolutionary algorithms, part two