An Alternative method in Multi-Attribute Decision Making using Data Envelopment Analysis and Fuzzy concept

TL;DR

This paper proposes a hybrid DEA-fuzzy model to improve decision-making evaluation of units with multiple inputs and outputs, addressing limitations of traditional DEA in MADM contexts.

Contribution

It introduces a novel hybrid approach combining DEA and fuzzy concepts for more reliable ranking in MADM applications.

Findings

Hybrid DEA-fuzzy model enhances ranking reliability

Self-assessment capability for each decision-making unit

Addresses limitations of traditional DEA in MADM

Abstract

Data Envelopment Analysis (DEA) as mathematical models evaluates the technical efficiency of Decision Making Units (DMU) having multiple inputs and multiple outputs. Researchers are interested in applying DEA models in Multi Attribute Decision Making (MADM) environment, but evaluation by these models is different in nature than MADM. This is why the results are not satisfactory. In this paper first, a challenging discussion is provided to indicate ranking using traditional DEA models is not reliable, and then a hybrid model using DEA and fuzzy concepts is proposed to present a self-assessment for each DMU.