Abstract
This paper considers a distributed convex optimization problem with a linearly coupled equality constraint and non-smooth objective function, in which heterogeneous time delays exist over the communication network. Based on the passivity of primal–dual dynamics, a distributed asynchronous algorithm that is robust to heterogeneous time delays over the network is proposed. By transforming the output information using the scattering variables and transmitting the scattering variables across the network, convergence to the optimal solution can be guaranteed with a distributed asynchronous method. Moreover, the convergence condition, which is irrelative to the heterogeneous delay parameters, is obtained through Lyapunov analysis. This means the proposed algorithm can achieve convergence to the optimal solution without the heterogeneous delay information. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
| Original language | English |
|---|---|
| Pages (from-to) | 2853-2866 |
| Journal | Neural Computing and Applications |
| Volume | 36 |
| Issue number | 6 |
| Online published | 24 Nov 2023 |
| DOIs | |
| Publication status | Published - Feb 2024 |
| Externally published | Yes |
Funding
This work is supported by the National Natural Science Foundation of China (Grant No. 72301048), the Natural Science Foundation of Chongqing (Grant No. CSTB2023NSCQ-MSX0316), the Science and Technology Research Program of Chongqing Education Commission (Grant No. KJQN202300510), the Chongqing Social Science Planning Project (Grant No. 2023NDQN28), and the Chongqing Normal University Doctoral Start-up Program (Grant No. 22XWB027), and in part by the Australian Research Council under Grant Nos. DP200101197 and DE210100274.
Research Keywords
- Distributed optimization
- Heterogeneous delay
- Non-smooth analysis
- Passivity based method
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