Birna P. Kristinsdottir

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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 lie(More)
Algorithms for finding large feasible n-dimensional intervals for constrained nonlinear optimization are presented. The n-dimensional interval is iteratively enlarged about a seed point while a checking routine maintains feasibility. Two checking routines are discussed: an interval subdivision method and a global optimization method. Both checking routines(More)
Statement of scope and purpose In engineering and science, it is often necessary to estimate functions based on a small number of evaluation points. We provide an estimation procedure that bounds a function using a Lipschitz bracket. We prove that the best sampling strategy is to sample at the midpoint of a specific interval. Abstract A procedure to(More)
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