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Title: Adaptive fractional distributed optimization algorithm with directed spanning trees (English)
Author: Peng, Huaijin
Author: Wei, Yiheng
Author: Zhou, Shuaiyu
Author: Yue, Dongdong
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 61
Issue: 3
Year: 2025
Pages: 377-403
Summary lang: English
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Category: math
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Summary: Distributed optimization has garnered significant attention in past decade, yet existing algorithms mainly rely on Laplacian matrix information for parameter settings, limiting their adaptability and applicability. To design the fully distributed algorithm, this paper uses an adaptive weight framework based on directed spanning trees (DST), which not only solves the consensus optimization problem but also can be extended to solve the resource allocation problem. The innovative integration of Nabla fractional calculus further improves performance, enabling efficient discrete-time distributed optimization. Moreover, The proposed algorithms optimality and convergence properties have been rigorously analyzed, which demonstrates that they can converge to the optimal solution of the problem under consideration. Finally, numerical simulations are conducted to validate the algorithm's feasibility and superiority. (English)
Keyword: distribute optimization
Keyword: fractional calculus
Keyword: directed graphs
Keyword: directed spanning trees
Keyword: resource allocation
Keyword: fully distributed
MSC: 05C05
MSC: 05C20
MSC: 26A33
MSC: 90C26
DOI: 10.14736/kyb-2025-3-0377
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Date available: 2025-07-14T09:37:08Z
Last updated: 2025-07-14
Stable URL: http://hdl.handle.net/10338.dmlcz/153033
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