An inexact algorithm with proximal distances for variational inequalities
RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 1, pp. 159-176.

In this paper we introduce an inexact proximal point algorithm using proximal distances for solving variational inequality problems when the mapping is pseudomonotone or quasimonotone. Under some natural assumptions we prove that the sequence generated by the algorithm is convergent for the pseudomonotone case and assuming an extra condition on the solution set we prove the convergence for the quasimonotone case. This approach unifies the results obtained by Auslender et al. [Math Oper. Res. 24 (1999) 644–688] and Brito et al. [J. Optim. Theory Appl. 154 (2012) 217–234] and extends the convergence properties for the class of φ-divergence distances and Bregman distances.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2017078
Classification : 65K15
Mots-clés : Variational inequalities, proximal distance, proximal point algorithm, quasimonotone and pseudomonotone mapping
Papa Quiroz, E.A. 1 ; Mallma Ramirez, L. 1 ; Oliveira, P.R. 1

1
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     title = {An inexact algorithm with proximal distances for variational inequalities},
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Papa Quiroz, E.A.; Mallma Ramirez, L.; Oliveira, P.R. An inexact algorithm with proximal distances for variational inequalities. RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 1, pp. 159-176. doi : 10.1051/ro/2017078. http://www.numdam.org/articles/10.1051/ro/2017078/

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