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Distributed Alternating Direction Method of Multipliers

Author(s)
Wei, Ermin; Ozdaglar, Asuman E.
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Abstract
We consider a network of agents that are cooperatively solving a global unconstrained optimization problem, where the objective function is the sum of privately known local objective functions of the agents. Recent literature on distributed optimization methods for solving this problem focused on subgradient based methods, which typically converge at the rate O (1/√k), where k is the number of iterations. In this paper, k we introduce a new distributed optimization algorithm based on Alternating Direction Method of Multipliers (ADMM), which is a classical method for sequentially decomposing optimization problems with coupled constraints. We show that this algorithm converges at the rate O (1/k).
Date issued
2012-12
URI
http://hdl.handle.net/1721.1/90489
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
Proceedings of the 2012 51st IEEE Conference on Decision and Control (CDC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Wei, Ermin, and Asuman Ozdaglar. “Distributed Alternating Direction Method of Multipliers.” 2012 IEEE 51st IEEE Conference on Decision and Control (CDC) (December 2012).
Version: Author's final manuscript
ISBN
978-1-4673-2066-5
978-1-4673-2065-8
978-1-4673-2063-4
978-1-4673-2064-1
ISSN
0743-1546

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