TY - GEN
T1 - On distributed optimization under inequality and equality constraints via penalty 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 the agents are to minimize a sum of local objective functions subject to a global inequality constraint, a global equality constraint and a global constraint set. 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 penalty function. This algorithm allows the agents exchange information over networks with time-varying topologies and asymptotically agree on an optimal solution and the optimal value.
AB - We consider a multi-agent convex optimization problem where the agents are to minimize a sum of local objective functions subject to a global inequality constraint, a global equality constraint and a global constraint set. 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 penalty function. This algorithm allows the agents exchange information over networks with time-varying topologies and asymptotically agree on an optimal solution and the optimal value.
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M3 - Conference contribution
AN - SCOPUS:77957791600
SN - 9781424474264
T3 - Proceedings of the 2010 American Control Conference, ACC 2010
SP - 2434
EP - 2439
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 -