Asynchronous distributed algorithm for constrained optimization and its application

This study focuses on the distributed convex optimization problem with local boundary constraints and multiple inequality constraints, specifically considering scenarios involving communication delays and inconsistent updates between nodes. To tackle the problem with guaranteed constraint satisfacti...

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Veröffentlicht in:Science China. Technological sciences Jg. 68; H. 6; S. 1600401
Hauptverfasser: Wang, Ting, Li, Zhongmei, Nie, Rong, Du, Wenli
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Beijing Science China Press 01.06.2025
Springer Nature B.V
Schlagworte:
Algorithms
Communication
Constraints
Convergence
Convexity
Engineering
Lagrange multiplier
Nodes
Optimization
Optimization algorithms
Research Paper
Science
geometric convergence
distributed optimization
inequality constraints
gradient tracking
communication delay
ISSN:1674-7321, 1869-1900
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Zusammenfassung:This study focuses on the distributed convex optimization problem with local boundary constraints and multiple inequality constraints, specifically considering scenarios involving communication delays and inconsistent updates between nodes. To tackle the problem with guaranteed constraint satisfaction, a distributed asynchronous optimization algorithm is proposed based on the parameter projection method. Moreover, an asynchronous gradient tracking mechanism is employed to accelerate convergence. In the convergence analysis, an augmented synchronous system with virtual nodes is adopted to transform the delayed optimization problem into a problem without delays. Based on the generalized small gain theory, the proposed algorithm is proved to achieve a geometric convergence rate. Finally, numerical simulations and industrial experiments verify the effectiveness of the proposed algorithm.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1674-7321
1869-1900
DOI:10.1007/s11431-024-2852-1