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Averaging Schemes for Solving Fived Point and Variational Inequality Problems

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dc.creator Magnanti, Thomas L.
dc.creator Perakis, Georgia
dc.date 2004-05-28T19:33:50Z
dc.date 2004-05-28T19:33:50Z
dc.date 1994-07
dc.date.accessioned 2013-10-09T02:39:03Z
dc.date.available 2013-10-09T02:39:03Z
dc.date.issued 2013-10-09
dc.identifier http://hdl.handle.net/1721.1/5325
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description We develop and study averaging schemes for solving fixed point and variational inequality problems. Typically, researchers have established convergence results for solution methods for these problems by establishing contractive estimates for their algorithmic maps. In this paper, we establish global convergence results using nonexpansive estimates. After first establishing convergence for a general iterative scheme for computing fixed points, we consider applications to projection and relaxation algorithms for solving variational inequality problems and to a generalized steepest descent method for solving systems of equations. As part of our development, we also establish a new interpretation of a norm condition typically used for establishing convergence of linearization schemes, by associating it with a strong-f-monotonicity condition. We conclude by applying our results to transportation networks.
dc.format 2370284 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 296-94
dc.title Averaging Schemes for Solving Fived Point and Variational Inequality Problems
dc.type Working Paper


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