Evaluating decision-making units under uncertainty using fuzzy multi-objective nonlinear programming

This paper proposes a new method to evaluate decision-making units (DMUs) under uncertainty using fuzzy data envelopment analysis (DEA). In the proposed multi-objective nonlinear programming methodology, both the objective functions and the constraints are considered fuzzy. This model is comprehensi...

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Bibliographic Details
Published in:INFOR. Information systems and operational research Vol. 55; no. 1; pp. 1 - 15
Main Authors: Zerafat Angiz, Madjid Langroudi, Nawawi, Mohd Kamal Mohd, Khalid, Ruzelan, Mustafa, Adli, Emrouznejad, Ali, John, Robert, Kendall, Graham
Format: Journal Article
Language:English
Published: Taylor & Francis 01.01.2017
Subjects:
Fuzzy DEA
fuzzy multi-objective linear programming
membership function
possibility programming
ISSN:0315-5986, 1916-0615
Online Access:Get full text
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Summary:This paper proposes a new method to evaluate decision-making units (DMUs) under uncertainty using fuzzy data envelopment analysis (DEA). In the proposed multi-objective nonlinear programming methodology, both the objective functions and the constraints are considered fuzzy. This model is comprehensive in dealing with uncertainty, in the sense that coefficients of the decision variables in the objective functions and in the constraints, as well as the DMUs under assessment, are assumed to be fuzzy numbers with triangular membership functions. A comparison between the current fuzzy DEA models and the proposed method is illustrated by a numerical example.
ISSN:0315-5986
1916-0615
DOI:10.1080/03155986.2016.1240944