TY - GEN
T1 - On distributed optimization under inequality constraints via Lagrangian primal-dual methods
AU - Zhu, Minghui
AU - Martínez, Sonia
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
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M3 - Conference contribution
AN - SCOPUS:77957801250
SN - 9781424474264
T3 - Proceedings of the 2010 American Control Conference, ACC 2010
SP - 4863
EP - 4868
BT - Proceedings of the 2010 American Control Conference, ACC 2010
T2 - 2010 American Control Conference, ACC 2010
Y2 - 30 June 2010 through 2 July 2010
ER -