Data envelopment analysis and robust optimization: A review

Pejman Peykani, Emran Mohammadi, Reza Farzipoor Saen*, Seyed Jafar Sadjadi, Mohsen Rostamy-Malkhalifeh

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

45 Citations (Scopus)


This paper reviews the milestone approaches for handling uncertainty in data envelopment analysis (DEA). This paper presents the detailed classifications of robust data envelopment analysis (RDEA). RDEA is appropriate for measuring the efficiencies of decision-making units in the presence of the data and distributional uncertainties. This paper reviews scenario-based and uncertainty set of DEA models. It covers 73 studies from 2008 to 2019. The paper concludes with suggestions about the guidelines for future researches in the field of RDEA.

Original languageEnglish
Article numbere12534
JournalExpert Systems
Issue number4
Publication statusPublished - Aug 1 2020


  • continuous uncertainty
  • data envelopment analysis (DEA)
  • discrete uncertainty
  • robust DEA (RDEA)
  • robust optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Artificial Intelligence

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