Development of a Modified Fuzzy Data Envelopment Analysis Model Based on Uncertainty Modeling and a Novel Efficiency Function

Authors

https://doi.org/10.48314/anowa.v1i4.62

Abstract

Data Envelopment Analysis (DEA) is a well-established nonparametric method for evaluating the relative efficiency of Decision-Making Units (DMUs). Conventional DEA models assume deterministic input and output data, which is rarely the case in real-world applications characterized by uncertainty and ambiguity. To overcome this limitation, this paper proposes a new fuzzy DEA framework by developing a modified efficiency function that is able to explicitly incorporate data uncertainty through fuzzy numbers. A new weighted  cut-based efficiency measure is introduced, which transforms the fuzzy DEA model into an equivalent deterministic linear programming formulation. The theoretical properties of the proposed model, including feasibility, uniformity, and boundedness, are investigated. Numerical experiments based on simulated data demonstrate the effectiveness and robustness of the proposed approach compared with classical DEA and existing fuzzy DEA models. The proposed framework provides a flexible and reliable tool for evaluating efficiency in uncertain environments.

Keywords:

Data envelopment analysis, Fuzzy data envelopment analysis, Uncertainty modeling, Efficiency measurement, Linearization

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Published

2025-12-21

Issue

Vol. 1 No. 4 (2025): Annals of Optimization With Applications (ANOWA)

Section

Articles

How to Cite

Abdolmaleki, E. ., Edalatpanah, S. A. ., & Ghaziani, K. . (2025). Development of a Modified Fuzzy Data Envelopment Analysis Model Based on Uncertainty Modeling and a Novel Efficiency Function. Annals of Optimization With Applications, 1(4), 288-300. https://doi.org/10.48314/anowa.v1i4.62