Neutrosophic perspective on DEA

Several attempts have been made to deal with uncertain input and output data in Data Envelopment Analysis (DEA). However, due to the limitation of these methods, they cannot be applied for solving DEA with indeterminacy, impreciseness, vagueness, inconsistent and incompleteness information. So this paper for the first time deals with the Neutrosophic Data Envelopment Analysis and present a new model to solve it.

[1]  Jiamin Wang,et al.  A comparative study of robust efficiency analysis and Data Envelopment Analysis with imprecise data , 2017, Expert Syst. Appl..

[2]  Jun Ye,et al.  Trapezoidal neutrosophic set and its application to multiple attribute decision-making , 2014, Neural Computing and Applications.

[3]  Mumtaz Ali,et al.  A Novel Clustering Algorithm in a Neutrosophic Recommender System for Medical Diagnosis , 2017, Cognitive Computation.

[4]  S. A. Edalatpanah,et al.  A note on “A new method for solving fully fuzzy linear programming problems” , 2013 .

[5]  Shiv Prasad Yadav,et al.  A fuzzy DEA model with undesirable fuzzy outputs and its application to the banking sector in India , 2014, Expert Syst. Appl..

[6]  Ali Emrouznejad,et al.  Interfaces with Other Disciplines Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping : A case of Mozambican banks , 2015 .

[7]  Florentin Smarandache.  Neutrosophic social structures specificities , 2015 .

[8]  S. A. Edalatpanah,et al.  A New Two-Phase Method for the Fuzzy Primal Simplex Algorithm , 2012 .

[9]  Ying Luo,et al.  Fuzzy data envelopment analysis based upon fuzzy arithmetic with an application to performance assessment of manufacturing enterprises , 2009, Expert Syst. Appl..

[10]  C. Kao,et al.  A mathematical programming approach to fuzzy efficiency ranking , 2003 .

[11]  Olivier A. Girod,et al.  A Mathematical Programming Approach for Measuring Technical Efficiency in a Fuzzy Environment , 1998 .

[12]  Lourdes Campos,et al.  Linear programming problems and ranking of fuzzy numbers , 1989 .

[13]  Yusuf Subas,et al.  A ranking method of single valued neutrosophic numbers and its applications to multi-attribute decision making problems , 2016, International Journal of Machine Learning and Cybernetics.

[14]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[15]  Francisco Herrera,et al.  A Review of Hesitant Fuzzy Sets: Quantitative and Qualitative Extensions , 2016, Fuzzy Logic in Its 50th Year.

[16]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[17]  S. A. Edalatpanah,et al.  A nonlinear model for fully fuzzy linear programming with fully unrestricted variables and parameters , 2016 .

[18]  Dimitris K. Despotis,et al.  Data envelopment analysis with imprecise data , 2002, Eur. J. Oper. Res..

[19]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[20]  Jianqiang Wang,et al.  Evaluation of e-commerce websites: An integrated approach under a single-valued trapezoidal neutrosophic environment , 2017, Knowl. Based Syst..

[21]  J. Sengupta.  A fuzzy systems approach in data envelopment analysis , 1992 .

[22]  Ali Emrouznejad,et al.  Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years , 2008 .

[23]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[24]  Romualdas Bausys,et al.  Sustainable market valuation of buildings by the single-valued neutrosophic MAMVA method , 2017, Appl. Soft Comput..

[25]  William W. CooperKyung.  IDEA and AR-IDEA: Models for Dealing with Imprecise Data in DEA , 1999 .

[26]  Mohamed Dia.  A model of fuzzy data envelopment analysis , 2004 .

[27]  F. Smarandache,et al.  Neutrosophic Integer Programming Problem , 2017 .

[28]  Joe Zhu,et al.  Bounded and discrete data and Likert scales in data envelopment analysis: application to regional energy efficiency in China , 2017, Ann. Oper. Res..

[29]  F. Smarandache,et al.  SINGLE VALUED NEUTROSOPHIC GRAPHS , 2016 .

[30]  Florentin Smarandache,et al.  Neutrosophic Modal Logic , 2017 .

[31]  Adel Hatami-Marbini,et al.  The State of the Art in Fuzzy Data Envelopment Analysis , 2014 .

[32]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[33]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[34]  Florentin Smarandache,et al.  Neutrosophic set - a generalization of the intuitionistic fuzzy set , 2004, 2006 IEEE International Conference on Granular Computing.

[35]  Rajshekhar Sunderraman,et al.  Single Valued Neutrosophic Sets , 2010 .

[36]  Witold Pedrycz,et al.  A novel Data Envelopment Analysis model for evaluating industrial production and environmental management system , 2018 .

[37]  Adel Hatami Marbini.  Dual-Role Factors for Imprecise Data Envelopment Analysis , 2017 .

[38]  John S. Liu,et al.  Research fronts in data envelopment analysis , 2016 .

[39]  Kwai-Sang Chin,et al.  Fuzzy data envelopment analysis: A fuzzy expected value approach , 2011, Expert Syst. Appl..

[40]  F. Smarandache.  A Unifying Field in Logics: Neutrosophic Logic. , 1999 .

[41]  Per J. Agrell,et al.  A flexible cross-efficiency fuzzy data envelopment analysis model for sustainable sourcing , 2017 .

[42]  Tomoe Entani,et al.  Dual models of interval DEA and its extension to interval data , 2002, Eur. J. Oper. Res..

[43]  Chiang Kao,et al.  Interval efficiency measures in data envelopment analysis with imprecise data , 2006, Eur. J. Oper. Res..