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Conditional Extragradient Algorithms for Solving Constrained Variational Inequalities

Yunier Bello-Cruz(yunierbello***at***niu.edu)
R. Diaz Millan(rdiazmillan***at***gmail.com)
Hung M. Phan(hung_phan***at***uml.edu)

Abstract: In this paper, we generalize the classical extragradient algorithm for solving variational inequality problems by utilizing non-null normal vectors of the feasible set. In particular, conceptual algorithms are proposed with two different linesearches. We then establish convergence results for these algorithms under mild assumptions. Our study suggests that non-null normal vectors may significantly improve convergence if chosen appropriately.

Keywords: Armijo-type linesearch, extragradient algorithm, projection algorithms

Category 1: Complementarity and Variational Inequalities

Category 2: Convex and Nonsmooth Optimization

Category 3: Global Optimization

Citation:

Download: [PDF]

Entry Submitted: 08/31/2018
Entry Accepted: 08/31/2018
Entry Last Modified: 08/31/2018

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