English

Outer Approximation Methods for Solving Variational Inequalities Defined over the Solution Set of a Split Convex Feasibility Problem

Optimization and Control 2019-08-21 v1

Abstract

We study variational inequalities which are governed by a strongly monotone and Lipschitz continuous operator FF over a closed and convex set SS. We assume that S=CA1(Q)S=C\cap A^{-1}(Q) is the nonempty solution set of a (multiple-set) split convex feasibility problem, where CC and QQ are both closed and convex subsets of two real Hilbert spaces H1\mathcal H_1 and H2\mathcal H_2, respectively, and the operator AA acting between them is linear. We consider a modification of the gradient projection method the main idea of which is to replace at each step the metric projection onto SS by another metric projection onto a half-space which contains SS. We propose three variants of a method for constructing the above-mentioned half-spaces by employing the multiple-set and the split structure of the set SS. For the split part we make use of the Landweber transform.

Keywords

Cite

@article{arxiv.1908.07398,
  title  = {Outer Approximation Methods for Solving Variational Inequalities Defined over the Solution Set of a Split Convex Feasibility Problem},
  author = {Andrzej Cegielski and Aviv Gibali and Simeon Reich and Rafał Zalas},
  journal= {arXiv preprint arXiv:1908.07398},
  year   = {2019}
}
R2 v1 2026-06-23T10:52:17.243Z