In Overlapping Correlation Clustering (OCC), a number of objects are assigned to clusters. Two objects in the same cluster have correlated characteristics. As opposed to traditional clustering where objects are assigned to a single cluster, in OCC objects may be assigned to one or more clusters. In this paper, we present Biased Random-Key Genetic Algorithms for OCC. We present computational experiments such results outperformed the state of art methods for OCC.