A Distributed Algorithm for Convex Constrained Optimization Under Noise

We present a novel distributed algorithm for convex constrained optimization problems that are subject to noise corruption and uncertainties. The proposed scheme can be classified as a distributed stochastic approximation method, where a unique feature here is that we allow for multiple noise terms...

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Veröffentlicht in:	IEEE transactions on automatic control Jg. 61; H. 9; S. 2496 - 2511
Hauptverfasser:	Chatzipanagiotis, Nikolaos, Zavlanos, Michael M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.09.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Approximation Approximation algorithms Approximation methods Constraints Convergence Distributed algorithms Distributed optimization Economic models Lagrange multiplier Linear programming Mathematical analysis Mathematical models multi-agent systems Noise noisy communications Optimization stochastic approximation stochastic optimization Stochasticity Uncertainty
ISSN:	0018-9286, 1558-2523
Online-Zugang:	Volltext
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