A Fully Parallel Distributed Algorithm for Nonsmooth Convex Optimization With Coupled Constraints: Applications to Distributed Consensus-Based Optimization and Distributed Resource Allocation

This article aims at collaborative optimization of sum of convex functions over networks subject to globally coupled affine equality and inequality constraints whose partial information is known by each agent. The proposed discrete-time fully parallel distributed algorithm is the first of its kind i...

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Bibliographic Details
Published in:	IEEE transactions on automatic control Vol. 70; no. 10; pp. 6877 - 6884
Main Authors:	Alaviani, Seyyed Shaho, Kelkar, Atul G., Vaidya, Umesh
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.10.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Constraints Convergence Convex analysis Convex functions Convexity Cost function Coupled constraints Data mining Distributed algorithms distributed optimization fully parallel algorithms IEEE Senior Members Lipschitz condition Optimization Parallel algorithms Plug-in electric vehicles Power dispatch Resource allocation Resource management Training
ISSN:	0018-9286, 1558-2523
Online Access:	Get full text
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