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Complexity of convex optimization using geometry-based measures and a reference point

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dc.contributor Freund, Robert M.
dc.date 2004-05-28T19:30:22Z
dc.date 2004-05-28T19:30:22Z
dc.date 2001
dc.date.accessioned 2013-10-09T02:38:39Z
dc.date.available 2013-10-09T02:38:39Z
dc.date.issued 2013-10-09
dc.identifier http://papers2.ssrn.com/paper.taf?ABSTRACT%5FID=288134
dc.identifier http://hdl.handle.net/1721.1/5256
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description Our concern lies in solving the following convex optimization problem: minimize cx subject to Ax=b, x \in P, where P is a closed convex set. We bound the complexity of computing an almost-optimal solution of this problem in terms of natural geometry-based measures of the feasible region and the level-set of almost-optimal solutions, relative to a given reference point xr that might be close to the feasible region and/or the almost-optimal level set. This contrasts with other complexity bounds for convex optimization that rely on data-based condition numbers or algebraic measures, and that do not take into account any a priori reference point information. Keywords: Convex Optimization, Complexity, Interior-Point Method, Barrier Method.
dc.description Robert M. Freund.
dc.description Abstract in HTML and working paper for download in PDF available via World Wide Web at the Social Science Research Network.
dc.description Title from cover. "September 2001."
dc.description Includes bibliographical references (leaf 29).
dc.format 29 leaves
dc.format 1483558 bytes
dc.format application/pdf
dc.language eng
dc.publisher Massachusetts Institute of Technology, Operations Research Center
dc.relation Operations Research Center Working Paper;OR 358-01
dc.rights http://papers2.ssrn.com/paper.taf?ABSTRACT%5FID=288134
dc.title Complexity of convex optimization using geometry-based measures and a reference point


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