Cluster-based distributed augmented Lagrangian algorithm for a class of constrained convex optimization problems

We propose a distributed solution for a constrained convex optimization problem over a network of clustered agents each consisted of a set of subagents. The communication range of the clustered agents is such that they can form a connected undirected graph topology. The total cost in this optimizati...

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Veröffentlicht in:	Automatica (Oxford) Jg. 129; S. 109608
Hauptverfasser:	Moradian, Hossein, Kia, Solmaz S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.07.2021
Schlagworte:	Augmented Lagrangian Distributed constrained convex optimization Optimal resource allocation Penalty function methods Primal–dual solutions Distributed constrained convex optimization Optimal resource allocation Penalty function methods Augmented Lagrangian Primal–dual solutions
ISSN:	0005-1098, 1873-2836
Online-Zugang:	Volltext
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