Risk-averse stochastic optimal control: An efficiently computable statistical upper bound

نویسندگان

چکیده

In this paper, we discuss an application of the Stochastic Dual Dynamic Programming (SDDP) type algorithm to nested risk-averse formulations Optimal Control (SOC) problems. We propose a construction statistical upper bound for optimal value SOC This outlines approach solution long standing problem in that area research. The holds large class convex and monotone conditional risk mappings. Finally, show validity solve real-life stochastic hydro-thermal planning problem.

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ژورنال

عنوان ژورنال: Operations Research Letters

سال: 2023

ISSN: ['0167-6377', '1872-7468']

DOI: https://doi.org/10.1016/j.orl.2023.05.002