Evolutionary Computation is an exciting research field with the power to assist researchers in the task of solving hard optimization problems (i.e., problems where the exploitable knowledge about the solution space is very hard and/or expensive to obtain). However, Evolutionary Algorithms are rarely used outside the circle of knowledgeable practitioners, and in that way have not achieved a status of useful enough tool to assist “general” researchers. We think that part of the blame is the lack of practical implementations of research efforts reflecting a unifying common ground in the field. In this communication we present GUIDE, a software framework incorporating some of the latest results from the EC research community and offering a Graphical User Interface that allows the straightforward manipulation of evolutionary algorithms. From a high-level description provided by the user it generates the code that is needed to run an evolutionary algorithm in a specified existing ...