2017
5
2
0
60
Data Envelopment Analysis with Sensitive Analysis and Superefficiency in Indian Banking Sector
2
2
Data envelopment analysis (DEA) is nonparametric linear programming (LP) based technique for estimating the relative efficiency of different decision making units (DMUs) assessing the homogeneous type of multipleinputs and multipleoutputs. The procedure does not require a priori knowledge of weights, while the main concern of this nonparametric technique is to estimate the optimal weights of inputs and outputs through which the proper classifications of DMUs are possible. DMUs classification with DEA has many challenges in the case of volatility in the values of inputs and outputs. Sensitivity classifications (either efficient or inefficient) as well as returns to scale (RTS) classification (CRS, IRS and DRS) of DMUs are the prominent and vital challenges in DEA studies. Flexible and feasible convex regions with changing values of the reference units from the reference set of inefficient DMUs. This paper has proposed the issues of sensitivities regarding the above mentioned classifications of DMUs and assessing the technical efficiencies by using SBM case of DEA models. Superefficiency is estimated in case of input and output slacks approach measure and ranking was mad as per the superefficiency score. Validity of the proposed model is carried with the suitable numerical illustration.
1

1193
1206


Q. Farooq
Dar
Department of Statistics, Ramanujan School of Mathematical Science, Pondicherry University, India
Department of Statistics, Ramanujan School
Iran


T. Rao
Pad
Department of Statistics, Ramanujan School of Mathematical Science, Pondicherry University, India
Department of Statistics, Ramanujan School
Iran


A. Muhammad
Tali
Department of Statistics, Ramanujan School of Mathematical Science, Pondicherry University, India
Department of Statistics, Ramanujan School
Iran


Yaser
Hamid
Dept. of Computer Science, Islamic University of Science and Technology
Jammu and Kashmir, India
Dept. of Computer Science, Islamic University
Iran


F
Danish
Division of Statistics and Computer Science, SKUASTJammu, India
Division of Statistics and Computer Science,
Iran
Sensitivity analysis
Decision Making Units
Super Efficiency
Data Envelopment Analysis
Linear programming problems
classifications
Slacks Approach Measure
Resource allocation based on DEA for distance improvement to MPSS points considering environmental factors
2
2
This paper proposes a new resource allocation model which is based on data envelopment analysis (DEA) and concerns systems with several homogeneous units operating under supervision of a central unit. The previous studies in DEA literature deal with reallocating/allocating organizational resource to improve performance or maximize the total amount of outputs produced by individual units. In those researches, it is assumed that all data are discretionary. Resource allocation problem has a multiple criteria nature; thus to solve it, many intervening factors should be regarded. This paper not only develops resource allocation plan for systems with both discretionary and non discretionary data in their inputs, but also considers environmental factors as well. In addition, the overall distance from the decision making units (DMUs) to their most productive scale size (MPSS) points is taken into account and is minimized in this method. To find the best allocation plan, this paper applies multiple objective programming (MOLP). Numerical examples are employed to illustrate the application of this approach on real data.
1

1207
1230


Azam
Mottaghi
Faculty of Mathematics and Computer Science, Amirkabir University of Technology, 424 Hafez Avenue, 15914 Tehran, Iran
Faculty of Mathematics and Computer Science,
Iran


Reza
Ezzati
Department of Mathematics, Islamic Azad University, Karaj Branch, Karaj, Iran
Department of Mathematics, Islamic Azad University
Iran


Esmaeil
Khorram
Faculty of Mathematics and Computer Science, Amirkabir University of Technology, 424 Hafez Avenue, 15914 Tehran, Iran
Faculty of Mathematics and Computer Science,
Iran
Resource Allocation
DEA
MOLP
MPSS point
Undesirable outputs
Discretionary inputs
A DEAbases Approach for Multiobjective Design of Attribute Acceptance Sampling Plans
2
2
Acceptance sampling (AS), as one of the main fields of statistical quality control (SQC),involves a system of principles and methods to make decisions about accepting or rejecting alot or sample. For attributes, the design of a single AS plan generally requires determination ofsample size, and acceptance number. Numerous approaches have been developed foroptimally selection of design parameters in last decades. We develop a multiobjectiveeconomicstatistical design (MOESD) of the single AS plan to reach a wellbalancedcompromise between cost and quality features. Moreover, a simple and efficient DEAbasedalgorithm for solving the model is proposed. Through a simulation study, the efficiency ofproposed model is illustrated. Comparisons of optimal designs obtained using MOESD toeconomic model with statistical constraints reveals enhanced performance of the multiobjectivemodel.
1

1231
1242


S.
JafarianNamin
Faculty of Industrial Engineering, Yazd University, Yazd, Iran
Faculty of Industrial Engineering, Yazd University
Iran


A
Pakzad
Department of Indutrial Engineering, Kosar University of Bojnord, Bojnord,
Iran
Department of Indutrial Engineering, Kosar
Iran


M.S.
M.S. Fallah Nezhad
Faculty of Industrial Engineering, Yazd University, Yazd, Iran
Faculty of Industrial Engineering, Yazd University
Iran
Acceptance sampling
Single sampling plan
MOESD
DEA
Interval Malmquist Productivity Index in DEA
2
2
Data envelopment analysis is a method for evaluating the relative efficiency of a collection of decision making units. The DEA classic models calculate each unit’s efficiency in the best condition, meaning that finds a weight that the DMU is at its maximum efficiency. In this paper, utilizing the directional distance function model in the presence of undesirable outputs, the efficiency of each unit has been calculated in the best and worst condition and an efficiency interval for each DMU is designated and then with aid from these efficiency interval, we present an interval for each unit with a proportionate Malmquist productivity index, that these intervals indicate the progression or regression of each DMU.
1

1243
1256


N.
Aghayi
Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran
Department of Mathematics, Ardabil Branch,
Iran


B.H.
Maleki
Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran
Department of Mathematics, Ardabil Branch,
Iran
Interval data
Directional distance function
Undesirable Output
Malmquist Productivity Index
Efficiency analysis in multistage network DEAR models
2
2
In many organizations and financial institutions, it is in many cases more cost and time efficient to access ratio data. Therefore, it is of great importance to evaluate the performance of decisionmaking units (DMUs) which only have access to ratios of inputs to outputs or vice versa (for instance, ratio of employees to students, ratio of assets to liabilities and ratio of doctors to patients). In this paper, we will propose twostage network DEAR model with multiobjective linear programming (MOLP) structures. Then, introducing a production possibility set (PPS) in each network stage, we will compare efficiency values in network DEA and DEAR. In the end, through an applied study on 22 medical centers which treat special patients in three stages, we will suggest an outputoriented multistage network DEAR model under assumption of CRS technology. The medical centers are evaluated in all three stages based on overall network efficiency. The results of the analysis are presented and a future research in this field is discussed in the final section of the paper.
1

1257
1276


Mohammad Reza
Mozaffari
Department of Mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran
Department of Mathematics, Shiraz Branch,
Iran
mozaffari854@yahoo.com


masoud
Sanei
Islamic Azad Univercity, Central Tehran Branch
Islamic Azad Univercity, Central Tehran Branch
Iran
masoudsanei49@yahoo.com


josef
jablonsky
Department of Econometrics, University of Economics, Prague, Czech Republic.
Department of Econometrics, University of
Iran
jablon@vse.cz
DEA
Network DEA
DEAR models
Efficiency
A general Approach to find NonZero Multiplier Weights in DEA
2
2
Data Envelopment Analysis (DEA) models can be stated as two mutually dual linear programs referred to as the envelopment and multiplier models. The multiplier models are stated in terms of variable input and output weights (multipliers). Zero multiplier weight for an input or output causes efficient problems in multiplier model. This paper concentrates on a previously proposed DEA model developed by Wang and Chin (2010) and later improved by Wang et al. (2011) to find nonzero multiplier weights. We will show that these models reveal shortcoming for certain classes of DMUs. In addition, we propose a general developed model to find a maximal element for a multiplier DEA model.
1

1277
1290


F.
Moradi
Department of Mathematics, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran.
Department of Mathematics, Sanandaj Branch,
Iran


S.
Shahghobadi
Department of Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
Department of Mathematics, Kermanshah Branch,
Iran
s.shahghobadi@iauksh.ac.ir
Data Envelopment Analysis
Maximal element
Crossefficiency.