10.57647/j.fomj.2025.0603.14

Development of a series-parallel data envelopment analysis model within an intuitionistic fuzzy environment

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  • Hoda Moradi1,
  • Hamid Babaei Meybodi*1,
  1. Department of Management, Meybod University, Meybod, Iran

Received: 2025-05-06

Revised: 2025-07-24

Accepted: 2025-08-17

Published in Issue 2025-09-30

Published Online: 2025-09-29

Copyright (c) 2025 Hoda Moradi, Hamid Babaei Meybodi (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Moradi, H., & Babaei Meybodi, H. (2025). Development of a series-parallel data envelopment analysis model within an intuitionistic fuzzy environment. Fuzzy Optimization and Modeling Journal (FOMJ), 6(3). https://doi.org/10.57647/j.fomj.2025.0603.14
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Abstract

Data Envelopment Analysis (DEA) is a widely used tool for evaluating the efficiency of Decision-Making Units. However, traditional DEA models often encounter limitations when applied to complex, multi-stage systems, particularly in the presence of uncertainty and ambiguity in the data. To address these challenges, this study introduces a series–parallel DEA model that integrates both optimistic and pessimistic evaluations within an intuitionistic fuzzy environment. The model is specifically designed to provide a more accurate and nuanced assessment of multi-stage system efficiency, especially when handling diverse data types commonly encountered in real-world settings, including crisp, fuzzy, and intuitionistic fuzzy data. Two numerical examples are presented to validate the proposed model: one based on synthetic data and another adapted from real-world data reported by Kao. These case studies illustrate the model’s effectiveness and practical applicability in evaluating the performance of multi-stage systems with complex and uncertain data. By incorporating both optimistic and pessimistic perspectives, the proposed framework offers a comprehensive and balanced evaluation of DMU performance, making it a valuable tool for decision-makers operating under uncertain and dynamic conditions.

Keywords

  • Data Envelopment Analysis,
  • Efficiency Evaluation,
  • Intuitionistic Fuzzy,
  • Multi-Stage Systems
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