A fuzzy expected value approach under generalized data envelopment analysis


Fuzzy data envelopment analysis (DEA) models emerge as another class of DEA models to account for imprecise inputs and outputs for decision making units (DMUs). Although several approaches for solving fuzzy DEA models have been developed, there are some drawbacks, ranging from the inability to provide satisfactory discrimination power to simplistic numerical examples that handles only triangular fuzzy numbers or symmetrical fuzzy numbers. To address these drawbacks, this paper proposes using the concept of expected value in generalized DEA (GDEA) model. This allows the unification of three models - fuzzy expected CCR, fuzzy expected BCC, and fuzzy expected FDH models - and the ability of these models to handle both symmetrical and asymmetrical fuzzy numbers. We also explored the role of fuzzy GDEA model as a ranking method and compared it to existing super-efficiency evaluation models. Our proposed model is always feasible, while infeasibility problems remain in certain cases under existing super-efficiency models. In order to illustrate the performance of the proposed method, it is first tested using two established numerical examples and compared with the results obtained from alternative methods. A third example on energy dependency among 23 European Union (EU) member countries is further used to validate and describe the efficacy of our approach under asymmetric fuzzy numbers.

Publication DOI: https://doi.org/10.1016/j.knosys.2015.06.025
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: © 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: data envelopment analysis,fuzzy expected value,generalized data envelopment analysis,super-efficiency,symmetric and asymmetric fuzzy numbers,Software,Artificial Intelligence,Management Information Systems,Information Systems and Management
Publication ISSN: 1872-7409
Last Modified: 01 Apr 2024 07:12
Date Deposited: 10 Aug 2015 11:15
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2015-11
Published Online Date: 2015-07-09
Authors: Ghasemi, M.-R.
Ignatius, Joshua
Lozano, Sebastián
Emrouznejad, Ali (ORCID Profile 0000-0001-8094-4244)
Hatami-Marbini, Adel



Version: Accepted Version

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