Data envelopment analysis with integer-valued factors in a fuzzy environment

2015 ◽  
Author(s):  
Sohrab Kordrostami ◽  
Monireh Jahani Sayyad Noveiri
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Fuzzy Environment

scholarly journals A FUZZY DATA ENVELOPMENT ANALYSIS FOR CLUSTERING OPERATING UNITS WITH IMPRECISE DATA

2013 ◽  
Vol 21 (01) ◽  
pp. 29-54 ◽  
Author(s):  
SABER SAATI ◽  
ADEL HATAMI-MARBINI ◽  
MADJID TAVANA ◽  
PER J. AGRELL
Keyword(s):  
Data Envelopment Analysis ◽  
Parametric Method ◽  
Data Envelopment ◽  
Output Data ◽  
Fuzzy Environment ◽  
Input And Output ◽  
Fuzzy Data Envelopment Analysis ◽  
Human Decision ◽  
Fuzzy Dea ◽  
Operating Units

Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiency of peer operating units that employ multiple inputs to produce multiple outputs. Several DEA methods have been proposed for clustering operating units. However, to the best of our knowledge, the existing methods in the literature do not simultaneously consider the priority between the clusters (classes) and the priority between the operating units in each cluster. Moreover, while crisp input and output data are indispensable in traditional DEA, real-world production processes may involve imprecise or ambiguous input and output data. Fuzzy set theory has been widely used to formalize and represent the impreciseness and ambiguity inherent in human decision-making. In this paper, we propose a new fuzzy DEA method for clustering operating units in a fuzzy environment by considering the priority between the clusters and the priority between the operating units in each cluster simultaneously. A numerical example and a case study for the Jet Ski purchasing decision by the Florida Border Patrol are presented to illustrate the efficacy and the applicability of the proposed method.

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