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dc.contributor.authorMagnanti, Thomas L.en_US
dc.contributor.authorPerakis, Georgiaen_US
dc.date.accessioned2004-05-28T19:33:50Z
dc.date.available2004-05-28T19:33:50Z
dc.date.issued1994-07en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/5325
dc.description.abstractWe 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.en_US
dc.format.extent2370284 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.publisherMassachusetts Institute of Technology, Operations Research Centeren_US
dc.relation.ispartofseriesOperations Research Center Working Paper;OR 296-94en_US
dc.titleAveraging Schemes for Solving Fived Point and Variational Inequality Problemsen_US
dc.typeWorking Paperen_US


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