A subgradient method with non-monotone line search
Optimization and Control
2022-04-22 v1
Abstract
In this paper we present a subgradient method with non-monotone line search for the minimization of convex functions with simple convex constraints. Different from the standard subgradient method with prefixed step sizes, the new method selects the step sizes in an adaptive way. Under mild conditions asymptotic convergence results and iteration-complexity bounds are obtained. Preliminary numerical results illustrate the relative efficiency of the proposed method.
Cite
@article{arxiv.2204.10009,
title = {A subgradient method with non-monotone line search},
author = {O. P. Ferreira and G. N. Grapiglia and E. M. Santos and J. C. O. Souza},
journal= {arXiv preprint arXiv:2204.10009},
year = {2022}
}