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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Vydané v:	IEEE transactions on automatic control Ročník 61; číslo 9; s. 2496 - 2511
Hlavní autori:	Chatzipanagiotis, Nikolaos, Zavlanos, Michael M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.09.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
On-line prístup:	Získať plný text
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