2013
1
4
4
93
The Calculation of Unit's Efficiency by Using the Interval Balance Index and the Interval TOPSIS
2
2
Data envelopment analysis (DEA) is a technique for measuring the efficiency of decision making units. In all models of the DEA, for each unit under assessment, the numerical efficiency is obtained which may be less than or equal to one. Given the possible large number of functional units, we use various ranking methods for evaluating units. One of the rating methods is Balance index and Topsis. This method has been used for categorical data. In this paper, we assume data as interval, introduce the interval Balance index and the interval Topsis and run it on a single example.
1

197
205


B.
Babazadehah
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Saveh, Iran
Department of Industrial Engineering, Science
Iran


E.
Najafi
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Department of Industrial Engineering, Science
Iran


M.
AhadzadehNamin
Department of mathematics, ShahreQodsBranch, Islamic Azad University, Tehran, Iran
Department of mathematics, ShahreQodsBranch,
Iran


Y.
jafari
Department of Mathematics, Shabestar Branch, Islamic Azad University, Shabestar, Iran
Department of Mathematics, Shabestar Branch,
Iran


E.
Ebrahimi
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Saveh, Iran
Department of Industrial Engineering, Science
Iran
Data Envelopment Analysis
Ranking
Interval data
Balance Index
TOPSIS
Estimating Returns to Scale in the Presence of Undesirable Factors in Data Envelopment Analysis
2
2
This research identifies returns to scale (RTS) of efficient decision making units (DMUs) with desirable (good) and undesirable (bad) inputs and outputs by presenting a new DEA (data envelopment analysis) approach. In this study, we first introduce a new inputoutput oriented model to determine efficient DMUs in the presence of undesirable factors and then, returns to scale of these DMUs are estimated by presenting a new nonradial DEA model. So far several RTS approaches has been proposed in DEA literature by many researchers, such as Banker and Thrall’s, Golany and Yu’s, Khodabakhshi’s et al., and Eslami and Khoveyni’s RTS approaches. In the proposed approaches, all inputs and outputs are respectively considered as desirable inputs and outputs while in real world, both desirable and undesirable data may be present. Note that advantage of our proposed approach is capable of estimating RTS of efficient DMUs in the presence of desirable and undesirable data. It is noticeable that, since an inefficient decision making unit (DMU) has more than one projection on the empirical function thus different returns to scales can be obtained for projections of the inefficient DMU by using our proposed RTS approach. Lastly, an empirical example for illustrating purpose is presented and also directions for future research are suggested.
1

207
226


R.
Eslami
Department of Mathematics, Islamic Azad University, South Tehran Branch, Tehran, Iran
Department of Mathematics, Islamic Azad University
Iran


A.
Davodabadi Farahani
Department of Mathematics, Islamic Azad University, South Tehran Branch, Tehran, Iran
Department of Mathematics, Islamic Azad University
Iran
Data envelopment analysis (DEA)
Returns to Scale (RTS)
Efficiency
Undesirable factors
Performance Evaluation of Sport Association Board of Isfahan Province through DEA and a Championship Approach
2
2
Performance evaluation in regular periods is one of the ways in which organizations can evaluate their performance as well as weak and strong points unifiedly and precisely. These days, mathematical models are also used to evaluate the efficiency and productivity of various units. These units are a collection of education, research and service activities as input and output factors and according to effectiveness and importance degree of each factor in total performance, the ratio of total weighed output to total weighed input are calculated as efficiency degree of decision making units. In this study, data envelopment analysis is employed to evaluate the efficiency of 48 sport association board of Isfahan province based on championship perspective. In present study, factors such as sending to matches, holding matches, the number of players in national teams and etc. are used. Moreover, calculation is done based on constant return on scale. Finding of efficiency calculation reveal that out of 50 present boards in Isfahan province, 24 boards in men's group and 22 boards in women's group have been efficient in year 90. After ranking blind and weaksighted board, deaf board and martial art board in women's group have been recognized in the first place. Also, blind and weaksighted board has the highest rank among 50 active association board in men's group. Finally sensitivity analysis of input data shows that sending to matches has the most significant effect on efficiency of association boards.
1

227
246


K.
Rezania
Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran
Department of Industrial Engineering, Najafabad
Iran


F.
Mokhatab Rafiei
Department of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan, Iran
Department of Industrial and Systems Engineering,
Iran


H.
Shirouyehzad
Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran
Department of Industrial Engineering, Najafabad
Iran
Performance evaluation efficiency
sport association board
Data Envelopment Analysis
Using NonArchimedean DEA Models for Classification of DMUs: A New Algorithm
2
2
A new algorithm for classification of DMUs to efficient and inefficient units in data envelopment analysis is presented. This algorithm uses the nonArchimedean CharnesCooperRhodes[1] (CCR) model. Also, it applies an assurance value for the nonArchimedean using only simple computations on inputs and outputs of DMUs (see [18]). The convergence and efficiency of the new algorithm show the advantage of this algorithm compared to the Thrall’s algorithm (see [23]).
1

247
257


S.
Mehrabian
Department of Math., Faculty of Mathematical Sci. & Computer,
Kharazmi University, Karaj, Iran
Department of Math., Faculty of Mathematical
Iran
Data Envelopment Analysis
Classification
Efficiency
NonArchimedean
Prioritizing Contractors Selection Using DEAR and AHP in Iranian Oil Pipelines and Telecommunication Company
2
2
Inthis article we offer a method of ranking contractors by using DEA based onanalysis deficit and AHP. The process of hierarchical analysis (AHP) byproviding scales from paired comparison matrix, performs the contractor’sprioritizing choice. But AHP has some problems and to solve those problems,Jahanshahloo and his colleagues presented a new model which uses DEA andstandard deviation. In this article, AHP’s scales are calculated with theextension of DEA based on analysis deficit DEAR (Ratio analysis). At the end,“Iranian Oil Pipeline and Telecommunication Company” contractors will be rankby the proposed method.
1

259
270


N.A.
Ashoori
Department of Managment, Science and Research Branch,Islamic Azad University,Fars, Iran
Department of Managment, Science and Research
Iran


M.R.
Mozaffari
Department of Managment, Science and Research Branch,Islamic Azad University,Fars, Iran
Department of Managment, Science and Research
Iran
Data envelopment analysis(DEA)
AHP
DEAR
Computation of Output Losses due to Congestion in Data Envelopment Analysis
2
2
Data Envelopment Analysis (DEA) is an approach for evaluating performances of Decision Making Units (DMUs). The performances of DMUs are affected by the amount of sources that DMUs used. Usually increases in inputs cause increases in outputs. However, there are situations where increases in one or more inputs generate a reduction in one or more outputs. In such situations there is congestion in inputs or production process. In this study, we review two approaches that are available in the DEA literature for evaluating congestion. Afterwards, we focus on output losses due to congestion, and a model is introduced to compute output reduction. Then, the mentioned models are applied on an empirical example and the results are presented and interpreted.
1

271
283


M.
Khodabakhshi
Department of Mathematics, Faculty of Mathematical Sciences, Shahid Beheshti University,G. C., Tehran, Iran
Department of Mathematics, Faculty of Mathematical
Iran


H.
Zare Haghighi
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Department of Mathematics, Science and Research
Iran
Data Envelopment Analysis
Decision Making Unit
Inefficiency
Congestion