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A Novel Ranking Method Based on Uncertain DEA Model

Publish Year: 1400
Type: Conference paper
Language: English
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CSIEM02_806

Index date: 17 July 2021

A Novel Ranking Method Based on Uncertain DEA Model abstract

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.

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A Novel Ranking Method Based on Uncertain DEA Model authors

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