In this paper we make use of extended similarity indices to calculate and track the internal similarity of evolutionary populations. Extended similarity metrics, which compare a stack of bitvectors, have the advantage that they do not require the full similarity matrix of the compound pool or aggregate metric. In addition to being more efficient, extended similarity metrics reduce to the traditional binary similarity metrics if applied to a set of two molecules. According to computational experiments, two newly proposed extended similarity metrics are highly advantageous compared to the extended Tanimoto similarity: the extended Baroni-Urbani-Buser similarity index and the extended Faith similarity index. Throughout this paper will make use of the extended Faith similarity index.