Extended Zero-Gradient-Sum Approach for Constrained Distributed Optimization with Free Initialization
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866913564259778560 |
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| author | Shi, Xinli Yu, Xinghuo Wen, Guanghui Xu, Xiangping |
| author_facet | Shi, Xinli Yu, Xinghuo Wen, Guanghui Xu, Xiangping |
| contents | This paper proposes an extended zero-gradient-sum (EZGS) approach for solving constrained distributed optimization (DO) with free initialization. A Newton-based continuous-time algorithm (CTA) is first designed for general constrained optimization and then extended to solve constrained DO based on the EZGS method. It is shown that for typical consensus protocols, the EZGS CTA can achieve the performance with exponential/finite/fixed/prescribed-time convergence. Particularly, the nonlinear consensus protocols for finite-time EZGS algorithms can have heterogeneous power coefficients. The prescribed-time EZGS dynamics is continuous and uniformly bounded, which can achieve the optimal solution in one stage. Moreover, the barrier method is employed to tackle the inequality constraints. Finally, the performance of the proposed algorithms is verified by numerical examples. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_13743 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Extended Zero-Gradient-Sum Approach for Constrained Distributed Optimization with Free Initialization Shi, Xinli Yu, Xinghuo Wen, Guanghui Xu, Xiangping Optimization and Control This paper proposes an extended zero-gradient-sum (EZGS) approach for solving constrained distributed optimization (DO) with free initialization. A Newton-based continuous-time algorithm (CTA) is first designed for general constrained optimization and then extended to solve constrained DO based on the EZGS method. It is shown that for typical consensus protocols, the EZGS CTA can achieve the performance with exponential/finite/fixed/prescribed-time convergence. Particularly, the nonlinear consensus protocols for finite-time EZGS algorithms can have heterogeneous power coefficients. The prescribed-time EZGS dynamics is continuous and uniformly bounded, which can achieve the optimal solution in one stage. Moreover, the barrier method is employed to tackle the inequality constraints. Finally, the performance of the proposed algorithms is verified by numerical examples. |
| title | Extended Zero-Gradient-Sum Approach for Constrained Distributed Optimization with Free Initialization |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2308.13743 |