Distributed Algorithm Over Time-Varying Unbalanced Graphs for Optimization Problem Subject to Multiple Local Constraints

This article addresses the optimization problem with its global objective function being composed of multiple convex functions under multiple nonidentical local constraints. The specific purpose is to resolve the studied optimization problem in a distributed manner in the presence of the time-varyin...

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Veröffentlicht in:IEEE transactions on control of network systems Jg. 12; H. 1; S. 387 - 402
Hauptverfasser: Liu, Hongzhe, Yu, Wenwu, Wen, Guanghui, Zheng, Wei Xing
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 01.03.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Constraints
Control systems
Convergence
Directed graphs
Distributed algorithms
Distributed optimization algorithm
improved push–pull framework
Linear programming
multiple local constraints
Network systems
Numerical simulation
Optimization
time-varying unbalanced graphs
Vectors
ISSN:2325-5870, 2372-2533
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Zusammenfassung:This article addresses the optimization problem with its global objective function being composed of multiple convex functions under multiple nonidentical local constraints. The specific purpose is to resolve the studied optimization problem in a distributed manner in the presence of the time-varying unbalanced graph sequence. For this purpose, an efficient distributed discrete-time algorithm is developed over the time-varying unbalanced graph sequence by improving the classical push-pull algorithms. Moreover, for the developed distributed discrete-time algorithm, a rigorous analysis is made of its convergence property to the optimal solution as well as its convergence rate under some standard assumptions. Finally, numerical simulations are carried out to demonstrate the good performance of the designed algorithm.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2325-5870
2372-2533
DOI:10.1109/TCNS.2024.3469048