CONSTRUCTING LARGE FEASIBLE SUBOPTIMAL INTERVALS FOR CONSTRAINED NONLINEAR OPTIMIZATION

An algorithm for finding a large feasible n-dimensional interval for constrained global optimization is presented. The n-dimensional interval is iteratively enlarged about a seed point while maintaining feasibility. An interval subdivision method may be used to check feasibility of the growing box. The resultant feasible interval is constrained to he within a given level set, thus ensuring it is close to the optimum. The ability to determine such a feasible interval is useful for exploring the neighbourhood of the optimum, and can be practically used in manufacturing considerations. The numerical properties of the algorithm are tested and demonstrated by an example problem.