Deriving robust and globalized robust solutions of uncertain linear programs having general convex uncertainty sets

B.L. Gorissen, J.P.C. Blanc, D. den Hertog, A. Ben-Tal

Research output: Contribution to journalArticleScientificpeer-review

16 Citations (Scopus)

Abstract

We propose a new way to derive tractable robust counterparts of a linear program based on the duality between the robust (“pessimistic”) primal problem and its “optimistic” dual. First we obtain a new convex reformulation of the dual problem of a robust linear program, and then show how to construct the primal robust solution from the dual optimal solution. Our result allows many new uncertainty regions to be considered. We give examples of tractable uncertainty regions that were previously intractable. The results are illustrated by solving a multi-item newsvendor problem. We also apply the new method to the
globalized robust counterpart scheme and show its tractability.
Original languageEnglish
Pages (from-to)672-679
JournalOperations Research
Volume62
Issue number3
Early online date29 Apr 2014
DOIs
Publication statusPublished - May 2014

Keywords

  • robust optimization
  • general convex uncertainty regions
  • uncertain linear optimizations
  • globalized robust counterpart

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