Pure adaptive search in monte carlo optimization
Patel, Nitin R.; Zabinsky, Zelda Barbara; Smith, Robert L.
1989-01
Citation
Patel, Nitin R.; Smith, Robert L.; Zabinsky, Zelda B.; (1989). "Pure adaptive search in monte carlo optimization." Mathematical Programming 43 (1-3): 317-328. <http://hdl.handle.net/2027.42/47920>
Abstract
Pure adaptive search constructs a sequence of points uniformly distributed within a corresponding sequence of nested regions of the feasible space. At any stage, the next point in the sequence is chosen uniformly distributed over the region of feasible space containing all points that are equal or superior in value to the previous points in the sequence. We show that for convex programs the number of iterations required to achieve a given accuracy of solution increases at most linearly in the dimension of the problem. This compares to exponential growth in iterations required for pure random search.Publisher
Springer-Verlag; The Mathematical Programming Society, Inc.
ISSN
1436-4646 0025-5610
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Article
Metadata
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