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

ABSTRACT

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.

KEYWORDS:

• Fuzzy DEA
• membership function
• fuzzy multi-objective linear programming
• possibility programming

Acknowledgments

This study was supported by Universiti Utara Malaysia. We wish to thank Universiti Utara Malaysia for sponsoring the corresponding author to participate and present the findings of the study in the 11th International Conference on Data Envelopment Analysis (DEA 2013) in Samsun, Turkey. Universiti Utara Malaysia had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.