A deterministic global optimization algorithm is introduced for locating global minimum potential energy molecular conformations. The proposed branch and bound type algorithm attains finite ε-convergence to the global minimum through the successive refinement of converging lower and upper bounds on the solution. These bounds are obtained through a novel convex lowering bounding of the total potential function and the subsequent solution of a series of nonlinear convex optimization problems. The minimization of the total potential energy function is performed on an independent set of internal coordinates involving only dihedral angles. A number of example problems illustrate the proposed approach.
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Maranas et al. (1994) studied this question.
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