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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Bibliographic Details
Published in:	IEEE transactions on network science and engineering Vol. 11; no. 5; pp. 4241 - 4251
Main Authors:	Qin, Yanfu, Lu, Kaihong, Wang, Hongxia
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.09.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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
Online Access:	Get full text
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