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. The 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.
Bibliographical noteThis is an Accepted Manuscript of an article published by Taylor & Francis in INFOR on 14/10/16, available online: http://www.tandfonline.com/10.1080/03155986.2016.1240944
- fuzzy DEA
- fuzzy multiobjective linear programming
- membership function
- possibility programming
Langroudi Zerafat Angiz, M., Nawawi, M. K. M., Khalid, R., Mustafa, A., Emrouznejad, A., John, R., & Kendall, G. (2017). Evaluating decision-making units under uncertainty using fuzzy multi-objective nonlinear programming. INFOR, 55(1), 1-15. https://doi.org/10.1080/03155986.2016.1240944