A Unifying Geometric Solution Framework and Complexity Analysis for Variational Inequalities

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5205

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DC Field	Value	Language
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	-
Appears in Collections:	MIT Items

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