A new data envelopment analysis method for ranking decision making units: An application in industrial parks

Mohammad Izadikhah, Reza Farzipoor Saen

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)


Relative efficiency of decision-making units (DMUs) is assessed by classical data envelopment analysis (DEA) models. DEA is a popular technique for efficiency evaluation. There might be a couple of efficient DMUs. Classical DEA models cannot fully rank efficient DMUs. In this paper, a novel technique for fully ranking all DMUs based on changing reference set using a single virtual inefficient DMU is proposed. To this end, the first concept of virtual DMU is defined as average of all inefficient DMUs. Virtual DMU is a proxy of all inefficient DMUs. This new method proposes a new ranking method that takes into account impact of efficient DMUs on virtual DMU and impact of efficient DMUs on influences of other efficient DMUs. A case study is given to show applicability of the proposed approach.

Original languageEnglish
Pages (from-to)596-608
Number of pages13
JournalExpert Systems
Issue number5
Publication statusPublished - Oct 2015


  • data envelopment analysis (DEA)
  • efficiency
  • industrial parks
  • ranking
  • reference set

ASJC Scopus subject areas

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

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