On The Behavior of Subgradient Projections Methods for Convex Feasibility Problems in Euclidean Spaces
Optimization and Control
2010-09-21 v1 Numerical Analysis
Abstract
We study some methods of subgradient projections for solving a convex feasibility problem with general (not necessarily hyperplanes or half-spaces) convex sets in the inconsistent case and propose a strategy that controls the relaxation parameters in a specific self-adapting manner. This strategy leaves enough user-flexibility but gives a mathematical guarantee for the algorithm's behavior in the inconsistent case. We present numerical results of computational experiments that illustrate the computational advantage of the new method.
Cite
@article{arxiv.0804.3647,
title = {On The Behavior of Subgradient Projections Methods for Convex Feasibility Problems in Euclidean Spaces},
author = {Dan Butnariu and Yair Censor and Pini Gurfil and Ethan Hadar},
journal= {arXiv preprint arXiv:0804.3647},
year = {2010}
}
Comments
SIAM Journal on Optimization, accepted for publication