Convergence and Bound Computation for Chance Constrained Distributionally Robust Models using Sample Approximation
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866917893325717504 |
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| author | Lei, Jiaqi Mehrotra, Sanjay |
| author_facet | Lei, Jiaqi Mehrotra, Sanjay |
| contents | This paper considers a distributionally robust chance constraint model with a general ambiguity set. We show that a sample based approximation of this model converges under suitable sufficient conditions. We also show that upper and lower bounds on the optimal value of the model can be estimated statistically. Specific ambiguity sets are discussed as examples. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_12018 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Convergence and Bound Computation for Chance Constrained Distributionally Robust Models using Sample Approximation Lei, Jiaqi Mehrotra, Sanjay Optimization and Control This paper considers a distributionally robust chance constraint model with a general ambiguity set. We show that a sample based approximation of this model converges under suitable sufficient conditions. We also show that upper and lower bounds on the optimal value of the model can be estimated statistically. Specific ambiguity sets are discussed as examples. |
| title | Convergence and Bound Computation for Chance Constrained Distributionally Robust Models using Sample Approximation |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2408.12018 |