toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author (up) Hosseinzadeh Lotfi, F.; Jahanshahloo, G.R.; Esmaeili, M. doi  openurl
  Title An alternative approach in the estimation of returns to scale under weight restrictions Type
  Year 2007 Publication Applied Mathematics and Computation Abbreviated Journal  
  Volume 189 Issue 1 Pages 719-724  
  Keywords Linear programming; Data Envelopment Analysis (DEA ); Returns to scale; Weight restrictions  
  Abstract This paper discusses the issue of returns to scale (RTS) under weight restrictions in data envelopment analysis (DEA). We first review Tone’s method [K. Tone, On returns to scale under weight restrictions in data envelopment analysis, Journal of Productivity Analysis 16 (2001) 31-47] for estimating returns to scale under weight restrictions. Then a new approach is introduced for this task, based upon the sum of the optimal lambda values in the weighted CCR model. The equivalence of this method and Tone?s method is proved. We then apply the method to a real world data set.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ Hosseinzadeh-LotfiJahanshahlooEsmaeili2007 Serial 3765  
Permanent link to this record
 

 
Author (up) Hosseinzadeh Lotfi, F.; Jahanshahloo, G.R.; Esmaeili, M. doi  openurl
  Title Sensitivity analysis of efficient units in the presence of non-discretionary inputs Type
  Year 2007 Publication Applied Mathematics and Computation Abbreviated Journal  
  Volume 190 Issue 2 Pages 1185-1197  
  Keywords Non-discretionary inputs; Data Envelopment Analysis (DEA ); Efficiency; Super-efficiency; Efficient frontier  
  Abstract Discretionary models of data envelopment analysis (DEA) assume that all inputs and outputs can be varied at the discretion of management or other users. In any realistic situation, however, there may exist ’exogenously fixed’ or non-discretionary factors that are beyond the control of a DMU’s management, which also need to be considered. This paper discusses and reviews the use of super-efficiency approach in data envelopment analysis (DEA) sensitivity analyses when some inputs are exogenously fixed. Super-efficiency data envelopment analysis (DEA) model is obtained when a decision making unit (DMU) under evaluation is excluded from the reference set. In this paper by means of modified Banker and Morey’s (BM hereafter) model [R.D. Banker, R. Morey, Efficiency analysis for exogenously fixed inputs and outputs, Operations Research 34 (1986) 513-521], in which the test DMU is excluded from the reference set, we are able to determine what perturbations of discretionary data can be tolerated before frontier DMUs become nonfrontier.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ Hosseinzadeh-LotfiJahanshahlooEsmaeili2007a Serial 3766  
Permanent link to this record
 

 
Author (up) Jahanshahloo, G.R.; Hosseinzadeh Lotfi, F.; Moradi, M. doi  openurl
  Title A DEA approach for fair allocation of common revenue Type
  Year 2005 Publication Applied Mathematics and Computation Abbreviated Journal  
  Volume 160 Issue 3 Pages 719-724  
  Keywords Data Envelopment Analysis (DEA ); Fair allocation of common revenue  
  Abstract An issue of considerable importance, how to allocate a common revenue in an equitable manner across a set of competing entities. This paper introduces a new approach to obtaining allocation common revenue on all decision making units (DMUs) in such a way that the relative efficiency is not changed. In this method for determining allocation common revenue dose not need to solving any linear programming. A numerical example is provided to illustrate the results of the analysis.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ JahanshahlooHosseinzadeh-LotfiMoradi2005 Serial 2998  
Permanent link to this record
 

 
Author (up) Jahanshahloo, G.R.; Hosseinzadeh Lotfi, F.; Moradi, M. doi  openurl
  Title Sensitivity and stability analysis in DEA with interval data Type
  Year 2004 Publication Applied Mathematics and Computation Abbreviated Journal  
  Volume 156 Issue 2 Pages 463-477  
  Keywords Data Envelopment Analysis (DEA ); Interval data; Sensitivity and radius stability analysis  
  Abstract In this paper, we find radius of stability for all decision making units, with interval data. In this approach, organization classification remains unchanged under perturbations of the interval data. Some numerical examples for illustration are given.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ JahanshahlooHosseinzadeh-LotfiMoradi2004 Serial 2660  
Permanent link to this record
 

 
Author (up) Jahanshahloo, G.R.; Hosseinzadeh Lotfi, F.; Rezai Balf, F.; Zhiani Rezai, H. doi  openurl
  Title Using Monte Carlo method for ranking interval data Type
  Year 2008 Publication Applied Mathematics and Computation Abbreviated Journal  
  Volume 201 Issue 1-2 Pages 613-620  
  Keywords Data Envelopment Analysis (DEA ); Ranking; Efficiency; Monte Carlo method; Interval data  
  Abstract Some methods have been presented for ranking efficient decision making units (DMUs) in data envelopment analysis (DEA). This paper addresses the ranking of interval data by using Monte Carlo method. This method is based on a paper [G.R. Jahanshahloo, F. Hosseinzadeh Lotfi, H. Zhiani Rezai, F. Rezai Balf, Using Monte Carlo method for ranking efficient DMUs, Applied Mathematics and Computation 162 (2005) 371-–379]. The worthwhile this method is its ability in ranking of extreme and non-extreme efficient DMUs.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ JahanshahlooHosseinzadeh-LotfiRezai-BalfZhiani-Rezai2008 Serial 4141  
Permanent link to this record
 

 
Author (up) Jahanshahloo, G.R.; Hosseinzadeh Lotfi, F.; Rezai Balf, F.; Zhiani Rezai, H. doi  openurl
  Title Discriminant analysis of interval data using Monte Carlo method in assessment of overlap Type
  Year 2007 Publication Applied Mathematics and Computation Abbreviated Journal  
  Volume 191 Issue 2 Pages 521-532  
  Keywords Data Envelopment Analysis (DEA ); Interval data; Discriminate analysis; Monte Carlo method  
  Abstract In this paper we show that the method of discriminant analysis (DA), on interval data by data envelopment analysis (DEA). DEA-discriminant analysis (DEA-DA) is designed to identify the existence or non-existence of an overlap between two groups, by separating hyperplane. In addition it predicts a new observation to the group which it belongs to. Data envelopment analysis technique which is developed based on the mathematical programming, evaluates the relative efficiency of a set of homogeneous decision making units. However, there are similarities between DEA and DA. DA is a method for separating two sets with previous knowledge meanwhile DEA is a technique for separating two sets efficient and inefficient without previous knowledge. Also goal programming method can be used for both of these methods.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ JahanshahlooHosseinzadeh-LotfiRezai-BalfZhiani-Rezai2007 Serial 3782  
Permanent link to this record
 

 
Author (up) Jahanshahloo, G.R.; Hosseinzadeh Lotfi, F.; Rezai, H.Z.; Balf, F.R. doi  openurl
  Title Finding strong defining hyperplanes of Production Possibility Set Type
  Year 2007 Publication European Journal of Operational Research Abbreviated Journal  
  Volume 177 Issue 1 Pages 42-54  
  Keywords Data Envelopment Analysis (DEA ); Production Possibility Set  
  Abstract Production Possibility Set (PPS) is defined as the set of all inputs and outputs of a system in which inputs can produce outputs. Data Envelopment Analysis models implicitly use PPS to evaluate relative efficiency of Decision Making Units (DMUs). Although DEA models can determine the efficiency of a DMU, they cannot present efficient frontiers of PPS. In this paper, we propose a method for finding all Strong Defining Hyperplanes of PPS (SDHP). They are equations that form efficient surfaces. These equations are useful in Sensitivity and Stability Analysis, the status of Returns to Scale of a DMU, incorporating performance information into the efficient frontier analysis and so on.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ JahanshahlooHosseinzadeh-LotfiRezaiBalf2007 Serial 3783  
Permanent link to this record
 

 
Author (up) Jahanshahloo, G.R.; Hosseinzadeh Lotfi, F.; Rezai, H.Z.; Balf, F.R. doi  openurl
  Title Using Monte Carlo method for ranking efficient DMUs Type
  Year 2005 Publication Applied Mathematics and Computation Abbreviated Journal  
  Volume 162 Issue 1 Pages 371-379  
  Keywords Data Envelopment Analysis (DEA ); Ranking; Efficiency; Monte Carlo method  
  Abstract For ranking efficient DMUs some methods have been developed. These methods are not able to rank non-extreme efficient DMUs. In this paper, using Monte Carlo method, a method has been developed which is able to rank all (extreme and non-extreme) efficient DMUs.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ JahanshahlooHosseinzadeh-LotfiRezaiBalf2005 Serial 2999  
Permanent link to this record
 

 
Author (up) Jahanshahloo, G.R.; Hosseinzadeh Lotfi, F.; Rostamy Malkhalifeh, M.; Ahadzadeh Namin, M. doi  openurl
  Title A generalized model for data envelopment analysis with interval data Type
  Year 2009 Publication Applied Mathematical Modelling Abbreviated Journal  
  Volume 33 Issue 7 Pages 3237-3244  
  Keywords Data Envelopment Analysis (DEA ); FDH; GDEA; Interval data  
  Abstract Data envelopment analysis (DEA) is a method to estimate the relative efficiency of decision-making units (DMUs) performing similar tasks in a production system that consumes multiple inputs to produce multiple outputs. So far, a number of DEA models with interval data have been developed. The CCR model with interval data, the BCC model with interval data and the FDH model with interval data are well known as basic DEA models with interval data. In this study, we suggest a model with interval data called interval generalized DEA (IGDEA) model, which can treat the stated basic DEA models with interval data in a unified way. In addition, by establishing the theoretical properties of the relationships among the IGDEA model and those DEA models with interval data, we prove that the IGDEA model makes it possible to calculate the efficiency of DMUs incorporating various preference structures of decision makers.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ JahanshahlooHosseinzadeh-LotfiRostamy-MalkhalifehAhadzadeh-Namin2009 Serial 4510  
Permanent link to this record
 

 
Author (up) Jahanshahloo, G.R.; Hosseinzadeh Lotfi, F.; Shahverdi, R.; Adabitabar, M.; Rostamy-Malkhalifeh, M.; Sohraiee, S. doi  openurl
  Title Ranking DMUs by I1-norm with fuzzy data in DEA Type
  Year 2009 Publication Chaos, Solitons & Fractals Abbreviated Journal  
  Volume 39 Issue 5 Pages 2294-2302  
  Keywords  
  Abstract The relative efficiency of a DMU is the result of comparing the inputs and outputs of the DMU and those of other DMUs in the PPS (production possibility set). If the inputs and outputs are fuzzy, the DMUs cannot be easily evaluated and ranked using the obtained efficiency scores. In this paper, presenting a new idea for ranking of DMUs with fuzzy data. And finally, we introduce a numerical example.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved  
  Call Number Admin @ admin @ JahanshahlooHosseinzadeh-LotfiShahverdiAdabitabarRostamy-MalkhalifehSohraiee2009 Serial 4511  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: