In this way, these methods come to be ideal candidates to be used for the parametrisation of ReaxFF potentials. This work is divided into two parts: In the first part, we propose a new procedure for optimising reactive force fields using evolutionary algorithms. The different algorithms are tested and evaluated on representative benchmark functions. Further, we extended the classical training by important solid-state properties such as bulk moduli, vibrational frequencies, or diffusion barriers to better describe the system's surface properties.