An adaptive online learning algorithm for distributed convex optimization with coupled constraints over unbalanced directed graphs

This paper investigates a distributed optimization problem over multi-agent networks subject to both local and coupled constraints in a non-stationary environment, where a set of agents aim to cooperatively minimize the sum of locally time-varying cost functions when the communication graphs are tim...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Journal of the Franklin Institute Jg. 356; H. 13; S. 7548 - 7570
Hauptverfasser:	Gu, Chuanye, Li, Jueyou, Wu, Zhiyou
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elmsford Elsevier Ltd 01.09.2019 Elsevier Science Ltd
Schlagworte:	Adaptive algorithms Algorithms Computational geometry Computer simulation Convexity Coupling Electric vehicle charging Electric vehicles Graph theory Graphs Machine learning Multiagent systems Nonstationary environments Optimization Studies
ISSN:	0016-0032, 1879-2693, 0016-0032
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!