Consistency of sample-based stationary points for infinite-dimensional stochastic optimization
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2023
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| _version_ | 1866909675107123200 |
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| author | Milz, Johannes |
| author_facet | Milz, Johannes |
| contents | We consider stochastic optimization problems with possibly nonsmooth integrands posed in Banach spaces and approximate these stochastic programs via a sample-based approaches. We establish the consistency of approximate Clarke stationary points of the sample-based approximations. Our framework is applied to risk-averse semilinear PDE-constrained optimization using the average value-at-risk and to risk-neutral bilinear PDE-constrained optimization. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_17032 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Consistency of sample-based stationary points for infinite-dimensional stochastic optimization Milz, Johannes Optimization and Control 65C05, 90C15, 35R60, 90C48, 90C30, 60H25, 49M41, 35Q93 We consider stochastic optimization problems with possibly nonsmooth integrands posed in Banach spaces and approximate these stochastic programs via a sample-based approaches. We establish the consistency of approximate Clarke stationary points of the sample-based approximations. Our framework is applied to risk-averse semilinear PDE-constrained optimization using the average value-at-risk and to risk-neutral bilinear PDE-constrained optimization. |
| title | Consistency of sample-based stationary points for infinite-dimensional stochastic optimization |
| topic | Optimization and Control 65C05, 90C15, 35R60, 90C48, 90C30, 60H25, 49M41, 35Q93 |
| url | https://arxiv.org/abs/2306.17032 |