Incorporating convex risk measures into multistage stochastic programming algorithms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Management Science and Operations Research,General Decision Sciences
Link
https://link.springer.com/content/pdf/10.1007/s10479-022-04977-w.pdf
Reference66 articles.
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3. Asamov, T., & Ruszczyński, A. (2015). Time-consistent approximations of risk-averse multistage stochastic optimization problems. Mathematical Programming, 153(2), 459–493.
4. Asienkiewicz, H., & Jaśkiewicz, A. (2017). A note on a new class of recursive utilities in Markov decision processes. Applicationes Mathematicae, 44, 149–161.
5. Balbás, A., Garrido, J., & Mayoral, S. (2009). Properties of distortion risk measures. Methodology and Computing in Applied Probability, 11(3), 385.
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