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Sensitivity analysis of Wasserstein distributionally robust optimization problems
We consider sensitivity of a generic stochastic optimization problem to model uncertainty. We take a non-parametric approach and capture model uncertainty using Wasserstein balls around the postulated model. We provide explicit formulae for the first-order correction to both the value function and t...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670962/ https://www.ncbi.nlm.nih.gov/pubmed/35153602 http://dx.doi.org/10.1098/rspa.2021.0176 |