  A computational method is presented which is capable to obtain low lying
energy structures of topological amorphous systems. The method merges a
differential mutation genetic algorithm with simulated annealing. This is done
by incorporating a thermal selection criterion, which makes it possible to
reliably obtain low lying minima with just a small population size and is
suitable for multimodal structural optimization. The method is tested on the
structural optimization of amorphous graphene from unbiased atomic starting
configurations. With just a population size of six systems, energetically very
low structures are obtained. While each of the structures represents a
distinctly different arrangement of the atoms, their properties, such as
energy, distribution of rings, radial distribution function, coordination
number and distribution of bond angles, are very similar.
