Iteration-complexity of a Rockafellar's proximal method of multipliers for convex programming based on second-order approximations
Optimization and Control
2016-02-23 v1
Abstract
This paper studies the iteration-complexity of a new primal-dual algorithm based on Rockafellar's proximal method of multipliers (PMM) for solving smooth convex programming problems with inequality constraints. In each step, either a step of Rockafellar's PMM for a second-order model of the problem is computed or a relaxed extragradient step is performed. The resulting algorithm is a (large-step) relaxed hybrid proximal extragradient (r-HPE) method of multipliers, which combines Rockafellar's PMM with the r-HPE method.
Keywords
Cite
@article{arxiv.1602.06794,
title = {Iteration-complexity of a Rockafellar's proximal method of multipliers for convex programming based on second-order approximations},
author = {M. Marques Alves and R. D. C. Monteiro and Benar F. Svaiter},
journal= {arXiv preprint arXiv:1602.06794},
year = {2016}
}