An Adaptive Continuous-Time Algorithm for Nonsmooth Convex Resource Allocation Optimization

This article develops a novel continuous-time algorithm based on the idea of adaptive strategy for solving a resource allocation optimization with nonsmooth objective functions and constraints over multiagent network. It is proved that the state solution is globally bounded and finally converges to...

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Veröffentlicht in:IEEE transactions on automatic control Jg. 67; H. 11; S. 6038 - 6044
Hauptverfasser: Jia, Wenwen, Liu, Na, Qin, Sitian
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.11.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Adaptive algorithms
Aerospace electronics
Complexity theory
Continuous-time algorithm
Convexity
Laplace equations
Linear programming
multiagent network
Multiagent systems
Optimization
Resource allocation
resource allocation optimization
Resource management
Technological innovation
ISSN:0018-9286, 1558-2523
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Zusammenfassung:This article develops a novel continuous-time algorithm based on the idea of adaptive strategy for solving a resource allocation optimization with nonsmooth objective functions and constraints over multiagent network. It is proved that the state solution is globally bounded and finally converges to an optimal solution to the nonsmooth convex resource allocation problem. Compared with the existing algorithms, the strong/strict convexity of the objective function is relaxed and only convexity is required. Moreover, by employing an exact penalty approach for the distributed optimization, the primal-dual variables is avoided to introduce. Therefore, the proposed algorithm has a simple structure with low dimensionality of state variables. To show the effectiveness and practicability of the presented algorithm, a numerical example and an application in power system are presented.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2021.3137054