A Parabolic Based Fuzzy Data Envelopment Analysis Model with an Application

A Fuzzy Data Envelopment Analysis (FDEA) is a popular technique to measure the relative efficiency of decisionmaking units (DMUs) with imprecise and vague data for multiple inputs and outputs. In real-life applications, there are two types of outputs: desirable outputs and undesirable outputs. In this paper, we have proposed a new version of FDEA model, named as Parabolic based Fuzzy Data Envelopment Analysis (PFDEA) model that computes parametric efficiency of a DMU in the presence of undesirable outputs. The inputs and outputs are represented in the form of asymmetric parabolic fuzzy numbers in the proposed model. A new technique is introduced to convert PFDEA model into a linear programming problem using α–cut approach with a novel section formula based method, named as Ratio Division Method. This method is used to perform the complete ranking of the DMUs in a numerical example using Cross-Efficiency Method to provide a complete ranking of the DMUs.

[1]  W. Cooper,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 1999 .

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

[3]  Richard H. Silkman,et al.  Measuring efficiency : an assessment of data envelopment analysis , 1986 .

[4]  Hervé Leleu,et al.  Shadow pricing of undesirable outputs in nonparametric analysis , 2013, Eur. J. Oper. Res..

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

[6]  Zilla Sinuany-Stern,et al.  Review of ranking methods in the data envelopment analysis context , 2002, Eur. J. Oper. Res..

[7]  Rolf Färe,et al.  Modeling undesirable factors in efficiency evaluation: Comment , 2004, Eur. J. Oper. Res..

[8]  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..

[9]  Yongjun Li,et al.  Increasing the discriminatory power of DEA in the presence of the undesirable outputs and large dimensionality of data sets with PCA , 2009, Expert Syst. Appl..

[10]  Holger Scheel,et al.  Undesirable outputs in efficiency valuations , 2001, Eur. J. Oper. Res..

[11]  Shiv Prasad Yadav,et al.  Fuzzy Mix-efficiency in Fuzzy Data Envelopment Analysis and Its Application , 2014 .

[12]  Ali Emrouznejad,et al.  Measurement efficiency and productivity in SAS/OR , 2005, Comput. Oper. Res..

[13]  Ali Emrouznejad,et al.  Economic Efficiency of smallholder maize producers in Western Kenya: a DEA meta-frontier analysis , 2009 .

[14]  Ali Emrouznejad,et al.  Fuzzy data envelopment analysis: A discrete approach , 2012, Expert Syst. Appl..

[15]  Isabelle Bloch,et al.  Fuzzy sets for image processing and understanding , 2015, Fuzzy Sets Syst..

[16]  F. Hosseinzadeh Lotfi,et al.  Ranking of units by positive ideal DMU with common weights , 2010, Expert Syst. Appl..

[17]  Hongliang Yang,et al.  Incorporating Both Undesirable Outputs and Uncontrollable Variables into Dea: the Performance of Chinese Coal-fired Power Plants Incorporating Both Undesirable Outputs and Uncontrollable Variables into Dea: the Performance of Chinese Coal-fired Power Plants , 2007 .

[18]  Eyke Hüllermeier,et al.  Fuzzy methods in machine learning and data mining: Status and prospects , 2005, Fuzzy Sets Syst..

[19]  Pekka J. Korhonen,et al.  ECO-EFFICIENCY ANALYSIS OF POWER PLANTS: AN EXTENSION OF DATA ENVELOPMENT ANALYSIS , 2000 .

[20]  Ali Emrouznejad,et al.  Performance Measurement with Fuzzy Data Envelopment Analysis , 2013 .

[21]  Adel Hatami-Marbini,et al.  A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making , 2011, Eur. J. Oper. Res..

[22]  S. You,et al.  A new approach in modelling undesirable output in DEA model , 2011, J. Oper. Res. Soc..

[23]  PuriJolly,et al.  A concept of fuzzy input mix-efficiency in fuzzy DEA and its application in banking sector , 2013 .

[24]  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..

[25]  Gholam Reza Jahanshahloo,et al.  Efficiency Analysis and Ranking of DMUs with Fuzzy Data , 2002, Fuzzy Optim. Decis. Mak..

[26]  F. Hosseinzadeh Lotfi,et al.  Undesirable inputs and outputs in DEA models , 2005, Appl. Math. Comput..

[27]  Shyh Hwang,et al.  An identification algorithm in fuzzy relational systems , 1996, Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium.

[28]  Jie Wu,et al.  A complete ranking of DMUs with undesirable outputs using restrictions in DEA models , 2013, Math. Comput. Model..

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

[30]  Mukesh Kumar,et al.  Measuring the efficiency of assembled printed circuit boards with undesirable outputs using data envelopment analysis , 2012 .

[31]  W Pedrycz,et al.  ON IDENTIFICATION IN FUZZY SYSTEMS AND ITS APPLICATIONS IN CONTROL PROBLEM, FUZZY SETS AND SYSTEMS , 1981 .

[32]  W. B. Liu,et al.  DEA models with undesirable inputs and outputs , 2010, Ann. Oper. Res..

[33]  T. Sexton,et al.  Data Envelopment Analysis: Critique and Extensions , 1986 .

[34]  Ali Emrouznejad,et al.  A comparative assessment of performance and productivity of health centres in Seychelles , 2007 .

[35]  W. Pedrycz,et al.  On identification in fuzzy systems and its applications in control problems , 1981 .

[36]  Shiv Prasad Yadav,et al.  Improved DEA models in the presence of undesirable outputs and imprecise data: an application to banking industry in India , 2017, Int. J. Syst. Assur. Eng. Manag..

[37]  Chiang Kao,et al.  Fuzzy efficiency measures in data envelopment analysis , 2000, Fuzzy Sets Syst..

[38]  F. Hosseinzadeh Lotfi,et al.  Efficiency and benchmarking in the presence of undesirable (bad) outputs: A DEA approach , 2012 .

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

[40]  Jie Wu,et al.  Determination of weights for ultimate cross efficiency using Shannon entropy , 2011, Expert Syst. Appl..