Distributed Resource Allocation via ADMM over Digraphs

In this paper, we solve the resource allocation problem over a network of agents, with edges as communication links that can be unidirectional. The goal is to minimize the sum of allocation cost functions subject to a coupling constraint in a distributed way by using the finite-time consensus-based...

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Bibliographic Details
Published inProceedings of the IEEE Conference on Decision & Control pp. 5645 - 5651
Main Authors Jiang, Wei, Doostmohammadian, Mohammadreza, Charalambous, Themistoklis
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.12.2022
Subjects
ADMM
Convex functions
Cost function
Couplings
digraphs
Directed graphs
Distributed optimization
finite-time consensus
Large-scale systems
Linear programming
resource allocation
Resource management
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ISSN2576-2370
DOI10.1109/CDC51059.2022.9993326

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Summary:In this paper, we solve the resource allocation problem over a network of agents, with edges as communication links that can be unidirectional. The goal is to minimize the sum of allocation cost functions subject to a coupling constraint in a distributed way by using the finite-time consensus-based alternating direction method of multipliers (ADMM) technique. In contrast to the existing gradient descent (GD) based distributed algorithms, our approach can be applied to non-differentiable cost functions. Also, the proposed algorithm is initialization-free and converges at a rate of \mathcal{O}\left( {1/k} \right), where k is the optimization iteration counter. The fast convergence performance related to iteration counter k compared to state-of-the-art GD based algorithms is shown via a simulation example.
ISSN:2576-2370
DOI:10.1109/CDC51059.2022.9993326