In comparing the performance of the different algorithms discussed in this paper, it is useful to differentiate whether algorithms encourage a significantly different amount of chemical diversity in their evolutionary populations. In cheminformatics, similarity between two molecules is usually quantified based on metrics applied to binary fingerprints that featurise chemical substructures. To calculate the diversity of molecules, the pairwise similarity of each combination of molecules in a set has been traditionally calculated using a binary similarity index, like the Tanimoto similarity , and summarised in an aggregate metric. However, the recent development of extended similarity metrics enables the simultaneous and straightforward comparison of an arbitrary number of bitvectors such as molecular finger-