Dual SDDP for risk-averse multistage stochastic programs
Optimization and Control
2023-04-21 v2
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.
Cite
@article{arxiv.2107.10930,
title = {Dual SDDP for risk-averse multistage stochastic programs},
author = {Bernardo Freitas Paulo da Costa and Vincent Leclère},
journal= {arXiv preprint arXiv:2107.10930},
year = {2023}
}
Comments
20 pages, 3 figures