Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations

Research output: Contribution to journalArticleScientificpeer-review

790 Citations (Scopus)
239 Downloads (Pure)

Fingerprint

Dive into the research topics of 'Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations'. Together they form a unique fingerprint.

INIS

Mathematics

Computer Science

Economics, Econometrics and Finance