On distributed optimization under inequality constraints via Lagrangian primal-dual methods
Minghui Zhu and Sonia Martínez
2010 American Control Conference, submitted
Abstract:
We consider a multi-agent convex optimization problem where agents are to minimize a sum of local objective functions subject to a global inequality constraint and a global constraint set. To deal with this, we devise a distributed primal-dual subgradient algorithm which is based on the characterization of the primal-dual optimal solutions as the saddle points of the Lagrangian function. This algorithm allows the agents to exchange information over networks with time-varying topologies and asymptotically agree on a pair of primal-dual optimal solutions and the optimal value.
File: main.pdf
Bib-tex entry:
@InProceedings{MZ-SM:10a-acc,
author = {M. Zhu and S. Mart{\'\i}nez},
booktitle = {Proceedings of the 2010 American Control Conference},
title = {On distributed optimization under inequality constraints via {L}agrangian primal-dual methods},
year = {2009},
address = {Baltimore, USA},
note = {Submitted}
}