Uncertain linear programs: Extended affinely adjustable robust counterparts

Xin Chen, Yuhan Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we introduce the extended affinely adjustable robust counterpart to modeling and solving multistage uncertain linear programs with fixed recourse. Our approach first reparameterizes the primitive uncertainties and then applies the affinely adjustable robust counterpart proposed in the literature, in which recourse decisions are restricted to be linear in terms of the primitive uncertainties. We propose a special case of the extended affinely adjustable robust counterpart - the splitting-based extended affinely adjustable robust counterpart - and illustrate both theoretically and computationally that the potential of the affinely adjustable robust counterpart method is well beyond the one presented in the literature. Similar to the affinely adjustable robust counterpart, our approach ends up with deterministic optimization formulations that are tractable and scalable to multistage problems.

Original languageEnglish (US)
Pages (from-to)1469-1482
Number of pages14
JournalOperations Research
Volume57
Issue number6
DOIs
StatePublished - Nov 2009

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research

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