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Pure adaptive search in monte carlo optimization

dc.contributor.authorPatel, Nitin R.en_US
dc.contributor.authorZabinsky, Zelda Barbaraen_US
dc.contributor.authorSmith, Robert L.en_US
dc.date.accessioned2006-09-11T19:33:11Z
dc.date.available2006-09-11T19:33:11Z
dc.date.issued1989-01en_US
dc.identifier.citationPatel, 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>en_US
dc.identifier.issn1436-4646en_US
dc.identifier.issn0025-5610en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/47920
dc.description.abstractPure 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.en_US
dc.format.extent567752 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherSpringer-Verlag; The Mathematical Programming Society, Inc.en_US
dc.subject.otherMathematical Methods in Physicsen_US
dc.subject.otherNumerical Analysisen_US
dc.subject.otherConvex Programmingen_US
dc.subject.otherMathematical and Computational Physicsen_US
dc.subject.otherCombinatoricsen_US
dc.subject.otherMonte Carlo Optimizationen_US
dc.subject.otherNumerical and Computational Methodsen_US
dc.subject.otherOperation Research/Decision Theoryen_US
dc.subject.otherRandom Searchen_US
dc.subject.otherCalculus of Variations and Optimal Controlen_US
dc.subject.otherOptimizationen_US
dc.subject.otherMathematics of Computingen_US
dc.subject.otherMathematicsen_US
dc.titlePure adaptive search in monte carlo optimizationen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Industrial and Operations Engineering, The University of Michigan, 48109, Ann Arbor, MI, USAen_US
dc.contributor.affiliationotherIndustrial Engineering Program, The University of Washington, Seattle, WA, USAen_US
dc.contributor.affiliationotherIndian Institute of Management, Ahmedabad, Indiaen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/47920/1/10107_2005_Article_BF01582296.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/BF01582296en_US
dc.identifier.sourceMathematical Programmingen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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