In the last years there has been great advance in the knowledge of the biological processes due to studies in computational simulations based on atomic description of molecular interactions. It is well known, that a macromolecular system can contain a huge amount of conformations, because of the enormous rotation degrees of freedom around chemical bonds, thus, leading to a great amount of local minimums in the molecular energy hyper-surface. Proteins express biological function in their native structure, the three-dimensional structure, which is generally found near the global energy minimum. In order to help solving the protein folding problem, we use a new strategy based on stochastic methods that allows finding the global energy minimum. In this strategy we use Generalized Simulated Annealing (GSA) coupled to the GROMOS96 force field to find the minimum energy conformation of a peptide that contain 22 alanines. To prevent the capture in local minimums of energy we use a parameter (qT), to control the freezing process. We scanned the values of "q" for the GSA parameters of visitation (qV) and acceptance (qA) in function of the temperature parameter (qT), where these values could vary from 1 to 3. We found the best "q" values to get the a-helix conformation for polyalanine, conformation which represents the global energy minimum. With GSA results, not only the configuration of lowest energy could be obtained, but also intermediate configurations, leading to a better understanding of the folding process. The GSA application in protein folding studies is of great relevance, since the number of computational cycles to reach a global minimum is extremely reduced.