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Fuzzy chance-constrained data envelopment analysis: a structured literature review, current trends, and future directions

Abstract

Fuzzy data envelopment analysis (FDEA) is one of the most applicable approaches for performance assessment of peer decision making units under ambiguity which is evolving rapidly and gaining popularity under uncertain data envelopment analysis field. The goal of this paper is to review some FDEA models based on applied possibility, necessity, credibility, general fuzzy measures and chance-constrained programming to deal with data ambiguity. The study presents a comprehensive and structured literature review of fuzzy chance-constrained data envelopment analysis (FCCDEA) studies including 87 studies from 2000 to 2020. The main contributions of this research include the following details: (1) Review of fuzzy chance-constrained programming, (2) Survey of FCCDEA models based on different fuzzy measures, (3) Analysis of FCCDEA applications and features, (4) Classification of FCCDEA studies from modeling and uncertainty type viewpoints, (5) Bibliometric analysis of FCCDEA literature, and (6) Extraction of main research gaps and guidelines for future research directions.

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The authors would like to thank the anonymous reviewers, associate editor, and the editor-in-chief for their constructive comments and suggestions.

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Peykani, P., Hosseinzadeh Lotfi, F., Sadjadi, S.J. et al. Fuzzy chance-constrained data envelopment analysis: a structured literature review, current trends, and future directions. Fuzzy Optim Decis Making 21, 197–261 (2022). https://doi.org/10.1007/s10700-021-09364-x

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  • DOI: https://doi.org/10.1007/s10700-021-09364-x

Keywords

  • Data envelopment analysis (DEA)
  • Fuzzy optimization
  • Fuzzy DEA (FDEA)
  • Chance-constrained programming (CCP)
  • Possibilistic programming
  • Fuzzy measure