An integrated fuzzy DEA-fuzzy AHP approach: a new model for ranking decision-making units

2013 ◽  
Vol 17 (1) ◽  
pp. 38 ◽  
Author(s):  
Seyed Mostafa Alem ◽  
Fariborz Jolai ◽  
Salman Nazari Shirkouhi
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
New Model ◽  
Fuzzy Dea ◽  
Decision Making Units

RANKING DECISION MAKING UNITS BY MEANS OF SOFT COMPUTING DEA MODELS

2011 ◽  
Vol 19 (01) ◽  
pp. 115-134 ◽  
Author(s):  
JOSÉ E. BOSCÁ ◽  
VICENTE LIERN ◽  
RAMÓN SALA ◽  
AURELIO MARTÍNEZ
Keyword(s):  
Decision Making ◽  
Statistical Analysis ◽  
Soft Computing ◽  
Ranking Method ◽  
Fuzzy Data ◽  
Trade Off ◽  
Dea Models ◽  
Data Efficiency ◽  
Fuzzy Dea ◽  
Decision Making Units

This paper presents a method for ranking a set of decision making units according to their level of efficiency and which takes into account uncertainty in the data. Efficiency is analysed using fuzzy DEA techniques and the ranking is based on the statistical analysis of cases that include representative situations. The method enables the removal of the sometimes unrealistic hypothesis of a perfect trade-off between increased inputs and outputs. This model is compared with other DEA models that work with imprecise or fuzzy data. As an illustration, we apply our ranking method to the evaluation of a group of Spanish seaports, as well as teams playing in the Spanish football league. We compare the results with other methods and we show that our method enables a total ranking of the seaports, and that the ranking of football teams is found to be more consistent with final league positions.

scholarly journals Eficiência técnica das companhias aéreas brasileiras: um estudo com análise envoltória de dados e conjuntos nebulosos

Production ◽  
2011 ◽  
Vol 21 (4) ◽  
pp. 676-683 ◽  
Author(s):  
Teresa Cristina Vilardo Domingues Correia ◽  
João Carlos Correia Baptista Soares de Mello ◽  
Lidia Angulo Meza
Keyword(s):  
Decision Making ◽  
Low Cost ◽  
Low Cost Carriers ◽  
Fuzzy Dea ◽  
Decision Making Units

Com a desregulamentação do transporte aéreo brasileiro, iniciada na década de 90, uma nova perspectiva de competição se desenvolveu, obrigando as empresas existentes a uma grande mudança em sua forma de posicionamento nesse tipo de mercado. Surge assim um novo conceito de voar com as companhias de baixo custo (Low Cost Carriers - LCCs) no mercado antes monopolizado pelas companhias tradicionais ou de serviço completo (Full Service Carriers - FSCs). Para garantir sua competitividade, as empresas viram-se obrigadas a buscar um melhor aproveitamento dos seus recursos. Este trabalho analisa, através do modelo DEA nebuloso, que leva em conta a má qualidade dos dados disponíveis, o desempenho das companhias aéreas brasileiras no período de 2001 a 2005. Além disso, dado que esse enfoque apresenta muitas unidades tomadoras de decisão (Decision Making Units - DMUs) empatadas, é sugerido um modelo de aumento de discriminação da análise envoltória de dados nebulosa (Fuzzy-DEA). É feita uma análise temporal dos dados de forma a avaliar a evolução das companhias aéreas frente ao novo cenário de competitividade no mercado.

scholarly journals A Novel Decision Support System Based on Fuzzy Multi Criteria Decision Making for Optimizing Machining Parameters

2021 ◽  
Author(s):  
Muhammed Ordu ◽  
◽  
Yusuf Fedai ◽  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Fuzzy Ahp ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Super Efficiency ◽  
Fuzzy Dea

The aim of this study is to develop a novel decision support system, which has never been developed yet, in order to optimize machining parameters. We combine the three distinct methods: experimental design and analysis, fuzzy data envelopment analysis (DEA) and fuzzy analytical hierarchy process (AHP). Firstly, a full factorial experiment including four factors and three levels is carried out. We take into account cutting speed, feed rate, depth of cut and number of cutting tool inserts as factors. The following three outputs are selected: Material Removal Rate, Machining Time and Surface Roughness. Secondly, a total of 23 experiments are determined as efficient decision-making units using fuzzy DEA with super efficiency method. Finally, a fuzzy AHP approach is conducted to rank the efficient experiments among each other. In conclusion, the results show that the Fuzzy DEA-Fuzzy AHP and the Fuzzy DEA with Super Efficiency generate clearly different rankings of experiments and Fuzzy DEA-Fuzzy AHP Approach has outperformed Fuzzy DEA with Super Efficiency Approach. The results highlight the importance of taking into account the expert opinions in the decision-making processes.

Fuzzy integer-valued data envelopment analysis

2018 ◽  
Vol 52 (4-5) ◽  
pp. 1429-1444 ◽  
Author(s):  
Sohrab Kordrostami ◽  
Alireza Amirteimoori ◽  
Monireh Jahani Sayyad Noveiri
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Real World ◽  
Data Envelopment ◽  
First Case ◽  
Dea Models ◽  
Analysis Models ◽  
Fuzzy Dea ◽  
Decision Making Units ◽  
Provided Examples

In conventional data envelopment analysis (DEA) models, the efficiency of decision making units (DMUs) is evaluated while data are precise and continuous. Nevertheless, there are occasions in the real world that the performance of DMUs must be calculated in the presence of vague and integer-valued measures. Therefore, the current paper proposes fuzzy integer-valued data envelopment analysis (FIDEA) models to determine the efficiency of DMUs when fuzzy and integer-valued inputs and/or outputs might exist. To illustrate, fuzzy number ranking and graded mean integration representation methods are used to solve some integer-valued data envelopment analysis models in the presence of fuzzy inputs and outputs. Two examples are utilized to illustrate and clarify the proposed approaches. In the provided examples, two cases are discussed. In the first case, all data are as fuzzy and integer-valued measures while in the second case a subset of data is fuzzy and integer-valued. The results of the proposed models indicate that the efficiency scores are calculated correctly and the projections of fuzzy and integer factors are determined as integer values, while this issue has not been discussed in fuzzy DEA, and projections may be estimated as real-valued data.

Extended DEA model under type-2 fuzzy environment

Kybernetes ◽  
2019 ◽  
Vol 48 (5) ◽  
pp. 1095-1133
Author(s):  
Xiaoqing Chen ◽  
Xinwang Liu ◽  
Zaiwu Gong
Keyword(s):  
Decision Making ◽  
Poverty Alleviation ◽  
Uncertain Information ◽  
Content Type ◽  
Dea Model ◽  
Efficiency Assessment ◽  
Fuzzy Dea ◽  
Decision Making Units ◽  
Balance Index

Purpose The purpose of this paper is to combine the uncertain methods of type-2 fuzzy sets and data envelopment analysis (DEA) evaluation model together. A new type-2 fuzzy DEA efficiency assessment method is established. Then the proposed procedure is applied to the poverty alleviation problem. Design/methodology/approach The research method is the DEA model, which is an effective method for efficiency assessment of social–economic systems. Considering the existence of the same efficiency values that cannot be ranked in the proposed DEA model, the balance index is introduced to solve the ranking problem of decision-making units effectively. Findings The results show that the proposed method can not only measure the efficiency of the existence of uncertain information but also deal with the ranking of multiple efficient decision-making units. Originality/value This paper selects type-2 fuzzy DEA model to express a lot of uncertain information in efficiency evaluation problems. We use the parameter decomposition method of type-2 fuzzy programming or the type-2 expectation values indirectly. The balance index is proposed to further distinguish the multiple effective decision-making units. Furthermore, this paper selects rural poverty alleviation in Hainan Province as a case study to verify the feasibility of the method. The relative efficiency values in different years are calculated and analyzed.

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

On Moderate Fuzzy Analytic Hierarchy Process Pairwise Comparison Model With Subcriteria

2016 ◽  
Vol 2 (3) ◽  
pp. 54
Author(s):  
G. Marimuthu ◽  
G. Ramesh
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Decision Models ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analysis Method ◽  
Analytic Hierarchy ◽  
Comparison Model ◽  
Hierarchy Process

Decisions usually involve the getting the best solution, selecting the suitable experiments, most appropriate judgments, taking the quality results etc., using some techniques.  Every decision making can be considered as the choice from the set of alternatives based on a set of criteria.  The fuzzy analytic hierarchy process is a multi-criteria decision making and is dealing with decision making problems through pairwise comparisons mode [10].  The weight vectors from this comparison model are obtained by using extent analysis method.  This paper concern with an alternate method of finding the weight vectors from the original fuzzy AHP decision model (moderate fuzzy AHP model), that has the same rank as obtained in original fuzzy AHP and ideal fuzzy AHP decision models.

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