Title :
A primal-dual algorithm for distributed optimization
Author :
Bianchi, P. ; Hachem, W.
Author_Institution :
LTCI, Telecom ParisTech., Paris, France
Abstract :
Consider a set of N agents who cooperate to solve the problem infx Σn=1N (fn (x) + gn (x)) where the convex cost functions (fn, gn) are local to the agent n. It is assumed that the functions fn are differentiable and have Lipschitz gradients. In this paper, a primal-dual algorithm for distributively solving this problem is proposed. This algorithm is an instance of a primal-dual algorithm separately introduced by Ṽu and Condat.
Keywords :
multi-agent systems; optimisation; set theory; Lipschitz gradients; convex cost functions; differentiable gradients; distributed optimization; primal-dual algorithm; Clustering algorithms; Convergence; Cost function; Equations; Minimization; Next generation networking; Radio frequency;
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
DOI :
10.1109/CDC.2014.7040050
