A complete ranking of DMUs using restrictions in DEA models

Alirezaee, Mohammad Reza; Afsharchi, Mohsen

doi:10.1016/j.amc.2006.12.031

Cited by 41 publications

(20 citation statements)

References 11 publications

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“…Jahanshahloo and Afzalinejad () presented a methodology for ranking DMUs by comparing them with full‐inefficient frontier. Alirezaee and Afsharian () suggested the balance index for ranking DMUs using restrictions in DEA models. Jahanshahloo et al .…”

Section: Introductionmentioning

confidence: 99%

A new data envelopment analysis method for ranking decision making units: an application in industrial parks

Izadikhah

Saen

2015

Expert Systems

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Relative efficiency of decision‐making units (DMUs) is assessed by classical data envelopment analysis (DEA) models. DEA is a popular technique for efficiency evaluation. There might be a couple of efficient DMUs. Classical DEA models cannot fully rank efficient DMUs. In this paper, a novel technique for fully ranking all DMUs based on changing reference set using a single virtual inefficient DMU is proposed. To this end, the first concept of virtual DMU is defined as average of all inefficient DMUs. Virtual DMU is a proxy of all inefficient DMUs. This new method proposes a new ranking method that takes into account impact of efficient DMUs on virtual DMU and impact of efficient DMUs on influences of other efficient DMUs. A case study is given to show applicability of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

A new data envelopment analysis method for ranking decision making units: an application in industrial parks

Izadikhah

Saen

2015

Expert Systems

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“…Reference [3] focused on the infeasible problems in super-efficiency DEA models. Reference [4,[7][8][9] further developed a general frame work to model and treat qualitative data in DEA. Recently, reference [5] made a theoretical comparison of TE using almost all existing models in DEA literature models and payed attention to the occurrence of multiple projections.…”

Section: Introductionmentioning

confidence: 99%

Classifying and ranking DMUs of different efficiency levels

Zhang

2010

2010 IEEE International Conference on Industrial Engineering and Engineering Management

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In this paper, we propose an alternative efficiency measurement to improve the insufficiency in Data Envelopment Analysis (DEA), provide a precise classification of efficient Decision Making Units (DMUs) and deliver more inner information about the evaluated DMUs, based on a new DEA non-traditional efficiency measurement which projects out DMUs at every input/output direction, one for each. Moreover, a procedure of three steps is given to differentiate the strongly efficient DMUs and weakly efficient DMUs among all the efficient reference sets. Finally, a numerical illustration is presented in this paper to show the potential advantages of the proposed DEA non-traditional efficiency measurement.

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“…Alirezaee and Afsharian [24] discussed multiplier model, in which the variables are considered as shadow prices; note that ∑ =1 and ∑ =1 V are total revenue and cost of DMU which are considered in optimization problem. The authors claimed that ∑ =1 − ∑ =1 V ≤ 0, = 1, .…”

Section: Ranking Techniques Based On Finding Optimal Weights In Dea Amentioning

confidence: 99%

“…Hosseinzadeh Lotfi et al [28] used a new method for ranking in order to find the best place for power plant location. Ali and Nakosteen [79], Amirteimoori et al [37] and Alirezaee and Afsharian [24], Soltanifar and Hosseinzadeh Lotfi [104], Zerafat Angiz et al [71], Hosseinzadeh Lotfi et al [28], Jahanshahloo [50], Chen and Deng [52], and Jablonsky [61] used different ranking methods in banking system. Sadjadi [40] ranked provincial gas companies in Iran.…”

Section: Different Applications In Ranking Unitsmentioning

confidence: 99%

A Review of Ranking Models in Data Envelopment Analysis

Lotfı

Jahanshahloo

Khodabakhshi

et al. 2013

Journal of Applied Mathematics

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In the course of improving various abilities of data envelopment analysis (DEA) models, many investigations have been carried out for ranking decision-making units (DMUs). This is an important issue both in theory and practice. There exist a variety of papers which apply different ranking methods to a real data set. Here the ranking methods are divided into seven groups. As each of the existing methods can be viewed from different aspects, it is possible that somewhat these groups have an overlapping with the others. The first group conducts the evaluation by a cross-efficiency matrix where the units are self-and peer-evaluated. In the second one, the ranking units are based on the optimal weights obtained from multiplier model of DEA technique. In the third group, superefficiency methods are dealt with which are based on the idea of excluding the unit under evaluation and analyzing the changes of frontier. The fourth group involves methods based on benchmarking, which adopts the idea of being a useful target for the inefficient units. The fourth group uses the multivariate statistical techniques, usually applied after conducting the DEA classification. The fifth research area ranks inefficient units through proportional measures of inefficiency. The sixth approach involves multiple-criteria decision methodologies with the DEA technique. In the last group, some different methods of ranking units are mentioned.

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A complete ranking of DMUs using restrictions in DEA models

Cited by 41 publications

References 11 publications

A new data envelopment analysis method for ranking decision making units: an application in industrial parks

A new data envelopment analysis method for ranking decision making units: an application in industrial parks

Classifying and ranking DMUs of different efficiency levels

A Review of Ranking Models in Data Envelopment Analysis

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