Distributionally robust stochastic dual dynamic programming

DANIEL DUQUE, DAVID P. MORTON

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We consider a multistage stochastic linear program that lends itself to solution by stochastic dual dynamic programming (SDDP). In this context, we consider a distributionally robust variant of the model with a finite number of realizations at each stage. Distributional robustness is with respect to the probability mass function governing these realizations. We describe a computationally tractable variant of SDDP to handle this model using the Wasserstein distance to characterize distributional uncertainty.

Original languageEnglish (US)
Pages (from-to)2841-2865
Number of pages25
JournalSIAM Journal on Optimization
Volume30
Issue number4
DOIs
StatePublished - Oct 7 2020

Keywords

  • Distributionally robust optimization
  • Multistage stochastic programming
  • Stochastic dual dynamic programming

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science

Fingerprint

Dive into the research topics of 'Distributionally robust stochastic dual dynamic programming'. Together they form a unique fingerprint.

Cite this