An Augmented Lagrangian Coordination-Decomposition Algorithm for Solving Distributed Non-Convex Programs
Optimization and Control
2014-07-22 v1
Abstract
A novel augmented Lagrangian method for solving non-convex programs with nonlinear cost and constraint couplings in a distributed framework is presented. The proposed decomposition algorithm is made of two layers: The outer level is a standard multiplier method with penalty on the nonlinear equality constraints, while the inner level consists of a block-coordinate descent (BCD) scheme. Based on standard results on multiplier methods and recent results on proximal regularised BCD techniques, it is proven that the method converges to a KKT point of the non-convex nonlinear program under a semi-algebraicity assumption. Efficacy of the algorithm is demonstrated on a numerical example.
Keywords
Cite
@article{arxiv.1407.5418,
title = {An Augmented Lagrangian Coordination-Decomposition Algorithm for Solving Distributed Non-Convex Programs},
author = {Jean-Hubert Hours and Colin N. Jones},
journal= {arXiv preprint arXiv:1407.5418},
year = {2014}
}
Comments
In Proceedings of the American Control Conference 2014