Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5205
Title: A Unifying Geometric Solution Framework and Complexity Analysis for Variational Inequalities
Issue Date: 9-Oct-2013
Publisher: Massachusetts Institute of Technology, Operations Research Center
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.
URI: http://koha.mediu.edu.my:8181/xmlui/handle/1721
Other Identifiers: http://hdl.handle.net/1721.1/5205
Appears in Collections:MIT Items

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