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Dual SDDP for risk-averse multistage stochastic programs

Bernardo Freitas Paulo da Costa(bernardofpc***at***im.ufrj.br)
Vincent Leclere(vincent.leclere***at***enpc.fr)

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.

Keywords: Stochastic programming, Dynamic programming, SDDP, Risk measures, Duality

Category 1: Stochastic Programming

Category 2: Other Topics (Dynamic Programming )


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Entry Submitted: 07/22/2021
Entry Accepted: 07/22/2021
Entry Last Modified: 07/22/2021

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