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A data-driven approach for a class of stochastic dynamic optimization problems
Dynamic stochastic optimization models provide a powerful tool to represent sequential decision-making processes. Typically, these models use statistical predictive methods to capture the structure of the underlying stochastic process without taking into consideration estimation errors and model mis...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478012/ https://www.ncbi.nlm.nih.gov/pubmed/34602750 http://dx.doi.org/10.1007/s10589-021-00320-4 |