Abstract
Introducing genetic algorithms as a reliable and effective tool to find ordered equilibrium structures, we predict minimum energy configurations of the square shoulder system for different values of corona width λ. By varying systematically the pressure and choosing different values of λ we are able to identify complete sequences of minimum energy configurations. The results provide a deeper understanding of the system's strategies to arrange particles in an energetically optimised fashion, leading to the competing self-assembly scenarios of cluster formation vs. lane formation.