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...

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Vydané v:	Journal of the Franklin Institute Ročník 356; číslo 13; s. 7548 - 7570
Hlavní autori:	Gu, Chuanye, Li, Jueyou, Wu, Zhiyou
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elmsford Elsevier Ltd 01.09.2019 Elsevier Science Ltd
Predmet:	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
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