2009
DOI: 10.1590/s0101-82052009000100002
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An inexact interior point proximal method for the variational inequality problem

Abstract: Abstract.We propose an infeasible interior proximal method for solving variational inequality problems with maximal monotone operators and linear constraints. The interior proximal method proposed by Auslender, Teboulle and Ben-Tiba [3] is a proximal method using a distance-like barrier function and it has a global convergence property under mild assumptions. However, this method is applicable only to problems whose feasible region has nonempty interior. The algorithm we propose is applicable to problems whose… Show more

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Cited by 29 publications
(9 citation statements)
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“…ykgox which imply that the sequences (x i k ) k∈N and (ỹ i k ) k∈N have the same cluster points. From the definition of α k in Algorithm F,ỹ k does not satisfy the inequality (10), that is, for all…”
Section: The Linesearch and The Algorithm Linesearchmentioning
confidence: 99%
“…ykgox which imply that the sequences (x i k ) k∈N and (ỹ i k ) k∈N have the same cluster points. From the definition of α k in Algorithm F,ỹ k does not satisfy the inequality (10), that is, for all…”
Section: The Linesearch and The Algorithm Linesearchmentioning
confidence: 99%
“…The mixed equilibrium problems include fixed point problems, variational inequality problems, optimization problems, Nash equilibrium problems, noncooperative games, economics and the equilibrium problem as special cases (see [9][10][11][12][13][14][15][16][17][18][19]). In the last two decades, many articles have appeared in the literature on the existence of solutions of equilibrium problems; see, for example [13] and references therein.…”
Section: Introductionmentioning
confidence: 99%
“…The studies of gradient-type methods and variational inequalities are important topics in optimization theory; see, for example, [1][2][3][4][5][6][7][8][9][10][11][12] and the references mentioned therein. In the present paper, we study convergence of the subgradient method, introduced in [13] and known in the literature as the extragradient method (see also [14,Chapter 12]) to a solution of a variational inequality in a Hilbert space, under the presence of computational errors.…”
Section: Introductionmentioning
confidence: 99%