Reducing weight flexibility in fuzzy DEA

Saati, Saber; Memariani, Azizollah

doi:10.1016/j.amc.2003.12.052

Cited by 43 publications

(22 citation statements)

References 11 publications

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“…The resulting interval programming problem could be solved as a crisp LP model for a given  with some variable substitutions. Saati and Memariani [33] proposed a technique for finding a common set of weights in fuzzy DEA based on the -level approach with triangular fuzzy data. Liu [34] suggested a fuzzy DEA procedure to obtain the efficiency measures embedded with assurance region (AR) concept when some observations were triangular fuzzy numbers.…”

Section: Dea and Fdea Modelsmentioning

confidence: 99%

Assessing the Efficiency of commercial Tunisian Banks using Fuzzy Data Envelopment Analysis

Tlig¹,

Hamed²

2017

Data Envelopment Analysis and Decision Science

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The banking sector is of great importance to Tunisian's economy. Major commercial banks continue to spend high proportion of their budgets on new technologies and innovation in order to satisfy their customers and enhance their competitiveness. Consequently, performance analysis has become part of their management practices.This paper aims to evaluate the efficiency of commercial Tunisian banks in terms of several crisp and imprecise data. Two approaches of fuzzy data envelopment analysis (FDEA), the possibility approach and the approach based on relations between fuzzy numbers (BRONF), are used to obtain the efficiency score of each bank. The results show that, in a competitive environment, no-financial inputs and outputs should be taken into account in order to obtain credible and realistic efficiency scores.

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Section: Dea and Fdea Modelsmentioning

confidence: 99%

Assessing the Efficiency of commercial Tunisian Banks using Fuzzy Data Envelopment Analysis

Tlig¹,

Hamed²

2017

Data Envelopment Analysis and Decision Science

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“…Fuzzy mathematical programming approach [13] which incorporated fuzziness into a DEA model has been studied by Sengupta [14] and Triantis and Girod [15]. In some researches, interval programming in DEA have been used either to extend the interval data to fuzzy input and output data [16] or to transform the fuzzy CCR model into a crisp model [9,10,17] under a given α-level set. On the contrary, the α-cut approach and Zadeh's extension principle have been investigated to transform fuzzy input and output data into intervals and then transform fuzzy DEA model to a family of conventional crisp DEA models (see, for example, Kao and Liu [18][19][20][21], Wang et al [22], and Soleimani et al [23]).…”

Section: Literature Reviewmentioning

confidence: 99%

“…For model (17), if q U j 1, then q M j 1 and q L j 1 will be automatically satisfied. The model can therefore be simplified as [33]:…”

Section: Multi-objective Dea Model In Fuzzy Dynamic Environment With mentioning

confidence: 99%

Multi-objective data envelopment analysis model in fuzzy dynamic environment with missing values

Jafarian-Moghaddam

Ghoseiri

2011

Int J Adv Manuf Technol

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Data envelopment analysis (DEA) is an important managerial tool for evaluating and improving the performance of decision making units. The existing DEA models are mostly limited to static environment using crisp data and are time-consuming and also have weak discriminating power. The aim of this work is to introduce a new fuzzy dynamic DEA model with missing values, which benefits from strengths of multi-objective modeling to overcome weakness and drawbacks of the classic DEA models. To check for quality and accuracy of the proposed model, this paper offers a comparative study to compare the discriminating power and computational efforts of the model with two problems in the literature taken as benchmarks. Also, this paper presents a real application of the fuzzy dynamic DEA model for assessing and ranking the level of performance for 56 railways around the globe using real data gathered from credible sources. The numerical case illustrates the model and the result may be used by railways to improve their performance efficiency compared to the best in the sample. Results for the comparative study and the real case reveal significant improvement in computational time and discriminating power.

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“…So, obtaining a common set of weights (CSW) which all decision making units follow it, can be vital. In this section the method of Saati & Memarian is proposed to find such a common set of weights [8,9,10]. In this method, the flexibility of factors will be limited, through evaluation of their high weights.…”

Section: Obtaining Common Set Of Weights (Csw) In Fuzzy Deamentioning

confidence: 99%

“…In the second stage, similar set of weights is determined through compressing the weights ranges by solving a linear programming model. Using two-stage model proposed by Saati et al [8], the below model will be obtained at the end of the first stage: …”

Section: The Proposed Modelmentioning

confidence: 99%

Evaluation of efficiency of electricity distribution company. Using modified DEA approach in Fuzzy environment Case study: Electricity Distribution Company of Fars Province

Gharib¹,

Nejad²

2015

Journal of Fuzzy Set Valued Analysis

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In present research, a modified DEA model has been used to evaluate the efficiency of different regions of Fars electricity distribution company in a Fuzzy environment. This model eliminates the weak points of basic models of data envelopment analysis in calculation of a different collection of selected weights for different units. First, the efficiency of electricity distribution units was measured using classical model of data envelopment analysis, and then this action was performed using modified model. In classic model, 5 electricity distribution units out of 18 were considered as efficient areas (about 28%), while in modified model, only 1 unit (about 5.5%) was efficient. The average of unit efficiency in classical model was 0.74, while in modified model it was 0.36. It indicates that this model not only eliminates the mentioned weak point, but also it increases the differentiation potential of classical models.

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Reducing weight flexibility in fuzzy DEA

Cited by 43 publications

References 11 publications

Assessing the Efficiency of commercial Tunisian Banks using Fuzzy Data Envelopment Analysis

Assessing the Efficiency of commercial Tunisian Banks using Fuzzy Data Envelopment Analysis

Multi-objective data envelopment analysis model in fuzzy dynamic environment with missing values

Evaluation of efficiency of electricity distribution company. Using modified DEA approach in Fuzzy environment Case study: Electricity Distribution Company of Fars Province

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