K-adaptability in two-stage mixed-integer robust optimization

Anirudh Subramanyam, Chrysanthos E. Gounaris, Wolfram Wiesemann

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

We study two-stage robust optimization problems with mixed discrete-continuous decisions in both stages. Despite their broad range of applications, these problems pose two fundamental challenges: (i) they constitute infinite-dimensional problems that require a finite-dimensional approximation, and (ii) the presence of discrete recourse decisions typically prohibits duality-based solution schemes. We address the first challenge by studying a K-adaptability formulation that selects K candidate recourse policies before observing the realization of the uncertain parameters and that implements the best of these policies after the realization is known. We address the second challenge through a branch-and-bound scheme that enjoys asymptotic convergence in general and finite convergence under specific conditions. We illustrate the performance of our algorithm in numerical experiments involving benchmark data from several application domains.

Original languageEnglish (US)
Pages (from-to)193-224
Number of pages32
JournalMathematical Programming Computation
Volume12
Issue number2
DOIs
StatePublished - Jun 1 2020

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Software

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