Consensus-based algorithms for stochastic optimization problems
Fuente:
arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866914166192734208 |
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| author | Bonandin, Sabrina Herty, Michael |
| author_facet | Bonandin, Sabrina Herty, Michael |
| contents | We address an optimization problem where the cost function is the expectation of a random mapping. To tackle the problem two approaches based on the approximation of the objective function by consensus-based particle optimization methods on the search space are developed. The resulting methods are mathematically analyzed using a mean-field approximation and their connection is established. Several numerical experiments show the validity of the proposed algorithms and investigate their rates of convergence. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_10372 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Consensus-based algorithms for stochastic optimization problems Bonandin, Sabrina Herty, Michael Optimization and Control 82B40, 65K10, 60K35 We address an optimization problem where the cost function is the expectation of a random mapping. To tackle the problem two approaches based on the approximation of the objective function by consensus-based particle optimization methods on the search space are developed. The resulting methods are mathematically analyzed using a mean-field approximation and their connection is established. Several numerical experiments show the validity of the proposed algorithms and investigate their rates of convergence. |
| title | Consensus-based algorithms for stochastic optimization problems |
| topic | Optimization and Control 82B40, 65K10, 60K35 |
| url | https://arxiv.org/abs/2404.10372 |