Topographical Global Optimization for Constrained Problems
نویسنده
چکیده
In topographical global optimization a sample of points that superuniformly cover the region of interest, A, is used in combination with the function evaluations in these points to obtain a topographical graph of A from which candidate points are easily extracted for local minimizations. This paper discusses some of the problems in obtaining such a cover and presents some solutions. These solutions are based on rst obtaining a set of starting points in all subregions of A, and then covering the neighbourhood of these points with a minimum of e ort. These new methods extend the applicability of topographical global optimization to constrained problems.
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