Finding optimized configurations for variability-intensive systems without constraint violations using a Regulatory Algorithm (RGA)

Feature selection is one of the important challenges in variability-intensive systems. The FCORE model is used for the description of the functional and non-functional requirements of a system from a systems engineering point of view. In addition we demonstrate a solution for feature selection using a regulator algorithm (RGA). The RGA is a two dimensional evolutionary algorithm, with regulator genes controlling the structural genes. This allows a direct transfer of the FCORE model into the RGA, which optimizes the feature selection without constraint violations.