Subgradient method with feasible inexact projections for constrained convex optimization problems
Optimization and Control
2020-06-17 v1
Abstract
In this paper, we propose a new inexact version of the projected subgradient method to solve nondifferentiable constrained convex optimization problems. The method combine -subgradient method with a procedure to obtain a feasible inexact projection onto the constraint set. Asymptotic convergence results and iteration-complexity bounds for the sequence generated by the method employing the well known exogenous stepsizes, Polyak's stepsizes, and dynamic stepsizes are established.
Cite
@article{arxiv.2006.08770,
title = {Subgradient method with feasible inexact projections for constrained convex optimization problems},
author = {Ademir Alves Aguiar and Orizon Pereira Ferreira and Leandro da Fonseca Prudente},
journal= {arXiv preprint arXiv:2006.08770},
year = {2020}
}