Abstract
The search for the global minimum of a potential energy function is very difficult since the number of local minima grows exponentially with the molecule size. The present work proposes the application of genetic algorithm and tabu search methods, which called GAMCP (Genetic Algorithm with Matrix Coding Partitioning) [4], and TSVP (Tabu Search with Variable Partitioning) [5], respectively, for minimizing the molecular potential energy function. Computational results for problems with up to 200 degrees of freedom are presented and favorable compared with other three existing methods from the literature. Numerical results show that the proposed two methods are promising and produce high quality solutions with low computational costs.
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