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A Unifying Geometric Solution Framework and Complexity Analysis for Variational Inequalities

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dc.contributor.author Magnanti, Thomas L. en_US
dc.contributor.author Perakis, Georgia en_US
dc.date.accessioned 2004-05-28T19:27:59Z
dc.date.available 2004-05-28T19:27:59Z
dc.date.issued 1996-02 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/5205
dc.description.abstract In this paper, we propose a concept of polynomiality for variational inequality problems and show how to find a near optimal solution of variational inequality problems in a polynomial number of iterations. To establish this result we build upon insights from several algorithms for linear and nonlinear programs (the ellipsoid algorithm, the method of centers of gravity, the method of inscribed ellipsoids, and Vaidya's algorithm) to develop a unifying geometric framework for solving variational inequality problems. The analysis rests upon the assumption of strong-f-monotonicity, which is weaker than strict and strong monotonicity. Since linear programs satisfy this assumption, the general framework applies to linear programs. en_US
dc.format.extent 2566871 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US en_US
dc.publisher Massachusetts Institute of Technology, Operations Research Center en_US
dc.relation.ispartofseries Operations Research Center Working Paper;OR 276-93 en_US
dc.title A Unifying Geometric Solution Framework and Complexity Analysis for Variational Inequalities en_US
dc.type Working Paper en_US


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