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Dual SDDP for risk-averse multistage stochastic programs
1 : Centre dÉnseignement et de Recherche en Mathématiques et Calcul Scientifique
Ecole des Ponts ParisTech
2 : UFRJ
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.
