Online Distributed Optimization With Nonconvex Objective Functions Under Unbalanced Digraphs: Dynamic Regret Analysis

In this paper, the problem of online distributed optimization subject to a convex set is studied by employing a network of agents. Each agent's objective function is time-varying and nonconvex and the agents exchange information with their neighbors through a time-varying directed graph. Partic...

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Vydané v:	IEEE transactions on network science and engineering Ročník 11; číslo 5; s. 4241 - 4251
Hlavní autori:	Qin, Yanfu, Lu, Kaihong, Wang, Hongxia
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.09.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Benchmark testing Convexity Decentralized control Deviation Dynamic regrets Graph theory Heuristic algorithms Linear programming Multi-agent systems nonconvex optimization online distributed optimization Online services Optimization Signal processing algorithms Time measurement unbalanced graphs
ISSN:	2327-4697, 2334-329X
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