In this paper we propose a hybrid genetic algorithm for minimizing molecular potential energy functions. Experimental evidence shows that the global minimum of the potential energy of a molecule corresponds to its most stable conformation, which dictates its properties. The search for the global minimum of a potential energy function is very difficult since the number of local minima grows exponentially with molecule size. The proposed approach was successfully applied to two cases: (i) a simplified version of more general molecular potential energy functions in problems with up to 100 degrees of freedom, and (ii) a realistic potential energy function modeling two different molecules.

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