At each generation, the ability of an individual to be among the lowest energy configurations is assessed by calculating its potential energy. In order to avoid the exploration of highly improbable non-physical structures, e.g. with too close distances or steric overlaps, initial local relaxations are performed before assigning the energy. Indeed, the individuals modified by the genetic operators can be very distorted and far from LM of the fitness function, which prevents the algorithm from progressing rapidly to low energies by stagnation or by bouncing off the PES, 49 in a manner quite similar to a gradient descent with high learning rate. To improve this, the search space is consequently focused on the physically more meaningful regions that involve LM.