  We benchmark the dynamical simplex evolution (DSE) method with several of the
currently available algorithms to detect communities in complex networks by
comparing the fraction of correctly identified nodes for different levels of
``fuzziness'' of random networks composed of well defined communities. The
potential benefits of the DSE method to detect hierarchical sub structures in
complex networks are discussed.
