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- W2954197016 abstract "Multistage risk-averse optimal control problems with nested conditional risk mappings are gaining popularity in various application domains. Risk-averse formulations interpolate between the classical expectation-based stochastic and minimax optimal control. This way, risk-averse problems aim at hedging against extreme low-probability events without being overly conservative. At the same time, risk-based constraints may be employed either as surrogates for chance (probabilistic) constraints or as a robustification of expectation-based constraints. Such multistage problems, however, have been identified as particularly hard to solve. We propose a decomposition method for such nested problems that allows us to solve them via efficient numerical optimization methods. Alongside, we propose a new form of risk constraints which accounts for the propagation of uncertainty in time." @default.
- W2954197016 created "2019-07-12" @default.
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- W2954197016 date "2019-06-01" @default.
- W2954197016 modified "2023-10-05" @default.
- W2954197016 title "Risk-averse risk-constrained optimal control" @default.
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- W2954197016 doi "https://doi.org/10.23919/ecc.2019.8796021" @default.
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