A general descent framework for the monotone variational inequality problem |
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Authors: | Jia Hao Wu Michael Florian Patrice Marcotte |
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Affiliation: | (1) Centre de recherche sur les transports, Université de Montréal, C.P. 6128, H3C 3J7 Succursale, Montréal, Qué., Canada |
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Abstract: | We present a framework for descent algorithms that solve the monotone variational inequality problem VIPv which consists in finding a solutionv* v satisfyings(v*)T(v–v*) 0, for allv v. This unified framework includes, as special cases, some well known iterative methods and equivalent optimization formulations. A descent method is developed for an equivalent general optimization formulation and a proof of its convergence is given. Based on this unified logarithmic framework, we show that a variant of the descent method where each subproblem is only solved approximately is globally convergent under certain conditions.This research was supported in part by individual operating grants from NSERC. |
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Keywords: | Variational inequalities descent methods optimization |
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