Extrapolated Proportional-Integral Projected Gradient Method for Conic Optimization
Optimization and Control
2022-06-27 v3
Abstract
Conic optimization is the minimization of a convex quadratic function subject to conic constraints. We introduce a novel first-order method for conic optimization, named \emph{extrapolated proportional-integral projected gradient method (xPIPG)}, that automatically detects infeasibility. The iterates of xPIPG either asymptotically satisfy a set of primal-dual optimality conditions, or generate a proof of primal or dual infeasibility. We demonstrate the application of xPIPG using benchmark problems in model predictive control. xPIPG outperforms many state-of-the-art conic optimization solvers, especially when solving large-scale problems.
Cite
@article{arxiv.2203.04188,
title = {Extrapolated Proportional-Integral Projected Gradient Method for Conic Optimization},
author = {Yue Yu and Purnanand Elango and Behçet Açıkmeşe and Ufuk Topcu},
journal= {arXiv preprint arXiv:2203.04188},
year = {2022}
}