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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Vydáno v:INFOR. Information systems and operational research Ročník 55; číslo 1; s. 1 - 15
Hlavní autoři: Zerafat Angiz, Madjid Langroudi, Nawawi, Mohd Kamal Mohd, Khalid, Ruzelan, Mustafa, Adli, Emrouznejad, Ali, John, Robert, Kendall, Graham
Médium: Journal Article
Jazyk:angličtina
Vydáno: Taylor & Francis 01.01.2017
Témata:
Fuzzy DEA
fuzzy multi-objective linear programming
membership function
possibility programming
ISSN:0315-5986, 1916-0615
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Shrnutí: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