  Computationally efficient and automated generation of convex hulls is
desirable for high throughput materials discovery of thermodynamically stable
multi-species crystal structures. A convex hull genetic algorithm is proposed
that uses methodology adapted from multi-objective optimisation techniques to
optimise the convex hull itself as an object, enabling efficient discovery of
convex hulls for N >= 2 species. This method, when tested on a LiSi system
utilising pre-trained machine learned potentials, was found to be able to
efficiently discover reported structures as well as new potential LiSi
candidate structures.
