Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | 2022 IEEE 61st Conference on Decision and Control (CDC) |
| Publisher | IEEE |
| Pages | 5645-5651 |
| Number of pages | 7 |
| ISBN (Electronic) | 978-1-6654-6761-2 |
| DOIs | |
| Publication status | Published - 10 Jan 2023 |
| MoE publication type | A4 Article in a conference publication |
| Event | IEEE Conference on Decision and Control - Cancun, Mexico Duration: 6 Dec 2022 → 9 Dec 2022 Conference number: 61 |
Conference
| Conference | IEEE Conference on Decision and Control |
|---|---|
| Abbreviated title | CDC |
| Country/Territory | Mexico |
| City | Cancun |
| Period | 06/12/2022 → 09/12/2022 |
Keywords
- Couplings
- Directed graphs
- Linear programming
- Cost function
- Convex functions
- Large-scale systems
- Resource management
- Distributed optimization
- ADMM
- resource allocation
- finite-time consensus
- digraphs