A Polyhedral Approximation Framework for Convex and Robust Distributed Optimization

In this paper we consider a general problem set-up for a wide class of convex and robust distributed optimization problems in peer-to-peer networks. In this set-up convex constraint sets are distributed to the network processors who have to compute the optimizer of a linear cost function subject to...

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Veröffentlicht in:	arXiv.org
Hauptverfasser:	Bürger, Mathias, Notarstefano, Giuseppe, Allgöwer, Frank
Format:	Paper
Sprache:	Englisch
Veröffentlicht:	Ithaca Cornell University Library, arXiv.org 25.03.2013
Schlagworte:	Algorithms Approximation Cutting Distributed generation Economic models Mathematical analysis Microprocessors Optimization Peer to peer computing Position sensing Processors Remote sensors Robustness Social networks Wireless sensor networks
ISSN:	2331-8422
Online-Zugang:	Volltext
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