A novel fuzzy data envelopment analysis model with double frontiers for supplier selection

Nazanin Ahmady, Majid Azadi, Seyed Amir Hossein Sadeghi, Reza Farzipoor Saen

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)

Abstract

Selecting the best suppliers is a significant yet complex decision which requires careful consideration of various performance criteria. Hence, supplier selection is an important issue and has a strategic significance for every company. One of the techniques that can be used for selecting suppliers is data envelopment analysis (DEA). In this paper, to handle ambiguity and fuzziness in supplier selection problems, a novel fuzzy DEA approach with double frontiers for selecting suppliers is developed. Compared with the traditional DEA, the DEA approach with double frontiers can identify the best supplier appropriately and easily without the need to impose any weight restriction or the need to calculate the cross-efficiency matrix, which requires a large number of computations and may also result in inconsistent conclusions. A numerical example demonstrates the application of the proposed model.

Original languageEnglish
Pages (from-to)87-98
Number of pages12
JournalInternational Journal of Logistics Research and Applications
Volume16
Issue number2
DOIs
Publication statusPublished - 2013

Keywords

  • data envelopment analysis
  • DEA with double frontiers
  • fuzzy DEA
  • supplier selection

ASJC Scopus subject areas

  • Management Information Systems
  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Management Science and Operations Research

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