Molecular force field parametrization using multi-objective evolutionary algorithms

We suggest a novel tool for the parametrization of molecular force fields by using multi-objective optimization algorithms with a new set of physically motivated objective functions. The new approach is validated in the parametrization of the bonded terms for the homologous series of primary alcohols. Multi-objective evolutionary algorithms (MOEAs) and particularly multi-objective particle swarm optimization (MOPSO) are applied. The results show that in this case MOPSO finds solutions with higher convergence than the MOEA method. Physical analysis of the results confirms the performance of the MOPSO method and the choice of objective functions.