Designing a New Efficiency Ranking Method in Data Envelopment Analysis Using Fuzzy Inference System

Objective: Data envelopment analysis is a well-known method based on mathematicalprogramming to measure the efficiency of decision-making units. This approachidentifies some units as efficient units set. According to these units, it constitutes anefficient frontier. In this case, discernment between...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Mohammad Hossein Karimi Govareshaki, Saeed Roshandel
Formato: article
Lenguaje:FA
Publicado: University of Tehran 2020
Materias:
Acceso en línea:https://doaj.org/article/0bcda04dbbec4efc9616b764731eabda
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Objective: Data envelopment analysis is a well-known method based on mathematicalprogramming to measure the efficiency of decision-making units. This approachidentifies some units as efficient units set. According to these units, it constitutes anefficient frontier. In this case, discernment between efficient decision-making units are isimpossible because several decision-makers have the same efficiency score.Methods: This study presents a new method for ranking efficient units in fuzzy dataenvelopment analysis. In this study, using a fuzzy inference system for ranking efficientunits is proposed as a new method. In the proposed method, the efficient and inefficientunits are first separated from each other using data envelopment analysis. Then, theconcepts of fuzzy inference system are used to rank efficient units.Results: The information of inefficient units is in a way which the fuzzy dataenvelopment analysis fails to assign an equivalent value of one to these unit’s efficiency.According to this concept, in the proposed method, each of these inefficient units isconsidered as a rule, and the amount of these rules are fired by the efficient units, hasused as an indicator for their ranking.Conclusion: Finally, a numerical example is performed to check the accuracy of themodel's performance. In this example, the data used in one of the basic articles in thisfield were used and it was found that the results obtained from the proposed method arequite similar to the results of the mentioned research.