An ideal-seeking fuzzy data envelopment analysis framework

Adel Hatami-Marbini, Saber Saati, Madjid Tavana

Research output: Contribution to journalArticlepeer-review

83 Citations (Scopus)


Data envelopment analysis (DEA) is a widely used mathematical programming approach for evaluating the relative efficiency of decision making units (DMUs) in organizations. Crisp input and output data are fundamentally indispensable in traditional DEA evaluation process. However, the input and output data in real-world problems are often imprecise or ambiguous. In this study, we present a four-phase fuzzy DEA framework based on the theory of displaced ideal. Two hypothetical DMUs called the ideal and nadir DMUs are constructed and used as reference points to evaluate a set of information technology (IT) investment strategies based on their Euclidean distance from these reference points. The best relative efficiency of the fuzzy ideal DMU and the worst relative efficiency of the fuzzy nadir DMU are determined and combined to rank the DMUs. A numerical example is presented to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms.

Original languageEnglish
Pages (from-to)1062-1070
Number of pages9
JournalApplied Soft Computing Journal
Issue number4
Early online date4 Jan 2010
Publication statusPublished - 1 Sep 2010
Externally publishedYes


Dive into the research topics of 'An ideal-seeking fuzzy data envelopment analysis framework'. Together they form a unique fingerprint.

Cite this