Dual SDDP for risk-averse multistage stochastic programs

2021/07/22 by da Costa, Bernardo Freitas Paulo, Leclère, Vincent
#49N15 #90C15 #90C39 #FOS: Mathematics #Optimization and Control (math.OC)

paper · doi:10.48550/arxiv.2107.10930

Abstract

Risk-averse multistage stochastic programs appear in multiple areas and are challenging to solve. Stochastic Dual Dynamic Programming (SDDP) is a well-known tool to address such problems under time-independence assumptions. We show how to derive a dual formulation for these problems and apply an SDDP algorithm, leading to converging and deterministic upper bounds for risk-averse problems.

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