A note on “Supplier selection by the new AR-IDEA model”

Farzipoor Saen proposed a method based on data envelopment analysis for supplier selection in the presence of weight restrictions and imprecise data (Int J Adv Manuf Technol 39 (11–12):1061–1070). The aim of this note is to show a computational deficiency in calculating the value of the preference intensity parameter in that paper.

[1]  Jian-Bo Yang,et al.  Interval weight generation approaches based on consistency test and interval comparison matrices , 2005, Appl. Math. Comput..

[2]  Hossein Azizi,et al.  The interval efficiency based on the optimistic and pessimistic points of view , 2011 .

[3]  Reza Farzipoor Saen,et al.  Supplier selection by the new AR-IDEA model , 2008 .

[4]  Alireza Amirteimoori,et al.  Measuring the multi-component efficiency with shared inputs and outputs in data envelopment analysis , 2004, Appl. Math. Comput..

[5]  Chiang Kao,et al.  Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan , 2008, Eur. J. Oper. Res..

[6]  Alireza Amirteimoori,et al.  An extended shortest path problem: A data envelopment analysis approach , 2012, Appl. Math. Lett..

[7]  Alireza Amirteimoori,et al.  Production planning: a DEA-based approach , 2011 .

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

[9]  Alireza Amirteimoori,et al.  Data envelopment analysis in dynamic framework , 2006, Appl. Math. Comput..

[10]  Paul Rouse,et al.  Relative efficiency measurement: The problem of a missing output in a subset of decision making units , 2012, Eur. J. Oper. Res..

[11]  Jian-Bo Yang,et al.  Interval efficiency assessment using data envelopment analysis , 2005, Fuzzy Sets Syst..

[12]  Dimitris K. Despotis,et al.  Data envelopment analysis with missing values: An interval DEA approach , 2006, Appl. Math. Comput..

[13]  E. Ertugrul Karsak,et al.  Using data envelopment analysis for evaluating flexible manufacturing systems in the presence of imprecise data , 2008 .

[14]  Alireza Amirteimoori,et al.  An improvement to the cost efficiency interval: A DEA-based approach , 2006, Appl. Math. Comput..

[15]  Reza Farzipoor Saen,et al.  Developing a new data envelopment analysis methodology for supplier selection in the presence of both undesirable outputs and imprecise data , 2010 .

[16]  Hossein Azizi,et al.  A note on data envelopment analysis with missing values: an interval DEA approach , 2013 .

[17]  Ying-Ming Wang,et al.  Measuring the performances of decision-making units using interval efficiencies , 2007 .

[18]  Ying-Ming Wang,et al.  Improved DEA models for measuring interval efficiencies of decision-making units , 2013 .

[19]  Hossein Azizi,et al.  Measurement of overall performances of decision-making units using ideal and anti-ideal decision-making units , 2010, Comput. Ind. Eng..

[20]  Jian-Bo Yang,et al.  Measuring the performances of decision-making units using geometric average efficiency , 2007, J. Oper. Res. Soc..

[21]  Kwai-Sang Chin,et al.  A new approach for the selection of advanced manufacturing technologies: DEA with double frontiers , 2009 .

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

[23]  Alireza Amirteimoori.  DEA efficiency analysis: Efficient and anti-efficient frontier , 2007, Appl. Math. Comput..

[24]  Ying-Ming Wang,et al.  Measuring Malmquist productivity index: A new approach based on double frontiers data envelopment analysis , 2011, Math. Comput. Model..

[25]  Hossein Azizi,et al.  Improved data envelopment analysis models for evaluating interval efficiencies of decision-making units , 2011, Comput. Ind. Eng..

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