A new global-optimization procedure is devised to tackle nonconvex nonlinear programming problems. The proposed algorithm is based on interval analysis and is guaranteed to yield the global solution. Several new accelerating tools are introduced to significantly reduce the computational intensity associated with classical interval-based optimization techniques. These tools include a lower-bound test as well as a "distrust-region" method for deleting infeasible subspaces. In addition, a local search is employed to continuously update an upper bound on the solution and to provide a means of splitting the search space. Illustrative examples are solved to demonstrate the efficacy of this novel algorithm.