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Paper Information

Journal:   JOURNAL OF SCIENCES (ISLAMIC AZAD UNIVERSITY)   WINTER 2010 , Volume - , Number 74/2 (MATHEMATICS ISSUE); Page(s) 53 To 60.
 
Paper: 

DMUS WITH NETWORK STRUCTURE AND IMPRECISE DATA

 
 
Author(s):  RAZAVYAN SH., TOHIDI G.*
 
* MATHEMATICS DEPARTMENT, AZAD UNIVERSITY, TEHRAN CENTER BRANCH, TEHRAN, IRAN
 
Abstract: 

Introduction: Data envelopment analysis (DEA) is a new technique developed in operations research and management science over the last three decades for measuring productive efficiency. In some situations some inputs and outputs are unknown decision variables such as bounded data, ordinal data, and ratio bounded data, then the resulting DEA model is a non-linear and is called Imprecise DEA (IDEA). DEA treats each DMU as a black box by considering only the inputs consumed and outputs produced by each DMU. In a network model, we focus on the transformation process in the black box.
Aim: In some situations, DMUs have network structure and imprecise data. This paper wants to propose a method to evaluate these DMUs.
Material and Method: Network Data Envelopment Analysis (DEA) models allow the researcher to study the inside of the usual black-box (production process). In this paper, we deal with imprecise data on network, and propose a method for evaluation network Decision Making Units (DMUs) with imprecise data. This method uses standard linear programming DEA model by converting imprecise data into interval data.
Results: In this paper we obtain an envelopment model, which is a generalized form of the basic DEA model.
Conclusion: This paper considered a network DEA model and proposed model to compute interval efficiency for DMUs with network structure and imprecise data. Similar discussion can be developed for any network DEA model.

 
Keyword(s): DATA ENVELOPMENT ANALYSIS (DEA), NETWORK DEA, IMPRECISE DATA
 
References: 
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