Pejman Peykani - School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
Donya Rahmani - Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
Jafar Gheidar-Kheljani - Management and Industrial Engineering Department, Malek Ashtar University of Technology, Tehran, Iran
Armin Jabbarzadeh - Department of Automated Production Engineering, École de Technologie Supérieure (ETS), Montreal, Canada
Mohammad Hossein Karimi Gavareshki - School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Proposing a full ranking method to rank all the homogeneous decision-making units (DMUs) is one of the important issues in data envelopment analysis (DEA) field. It should be noted that one of the main challenges in using traditional ranking approaches to realworld applications is the presence of noise and uncertainty in some of the input/output data of DMUs. Thus, in this paper, the novel ranking method for DMUs under uncertain environment is presented. using DEA method, super efficiency technique, and uncertainty theory. Moreover, validation and verification of the proposed uncertain super-efficiency data envelopment analysis (USEDEA) modelis illustrated by applying a numerical example.

Data Envelopment Analysis; Super-Efficiency Technique; Uncertainty Distribution; Ranking Method.