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A Unifying Geometric Solution Framework and Complexity Analysis for Variational Inequalities

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dc.creator Magnanti, Thomas L.
dc.creator Perakis, Georgia
dc.date 2004-05-28T19:27:59Z
dc.date 2004-05-28T19:27:59Z
dc.date 1996-02
dc.date.accessioned 2013-10-09T02:38:25Z
dc.date.available 2013-10-09T02:38:25Z
dc.date.issued 2013-10-09
dc.identifier http://hdl.handle.net/1721.1/5205
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description 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.
dc.format 2566871 bytes
dc.format application/pdf
dc.language en_US
dc.publisher Massachusetts Institute of Technology, Operations Research Center
dc.relation Operations Research Center Working Paper;OR 276-93
dc.title A Unifying Geometric Solution Framework and Complexity Analysis for Variational Inequalities
dc.type Working Paper


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