Abstract
This work considers efficiency measures in data envelopment analysis with non-L-R type fuzzy data. It shows that the relative efficiencies of decision-making units with non-L-R type fuzzy inputs and outputs can be measured by solving an optimization problem on a mixed domain. The necessary and sufficient conditions for solving the resulting optimization problems are then investigated. This is the first attempt to measure fuzzy efficiency in data envelopment analysis in view of optimization problems on a mixed domain.
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References
Adivar M, Fang S-C (2012) Convex optimization on mixed domains. J Ind Manag Optim 44(1):189–227
Agarwal RP, Bohner M (1999) Basic calculus on time scales and some of its applications. Results Math 35:3–22
Bazaraa MS, Sherali HD, Shetty CM (2006) Nonlinear programming theory and algorithms, 3rd edn. Wiley-Interscience (John Wiley and Sons), Hoboken
Bohner M, Peterson AC (2001) Dynamic equations on time scales, an introduction with applications. Birkhauser Boston Inc., Boston
Bohner M, Peterson AC (2003) Advances in dynamic equations on time scales. Birkhauser Boston Inc., Boston
Cadenas JM, Verdegay JL (2009) Towards a new strategy for solving fuzzy optimization problems. Fuzzy Optim Decis Mak 8:231–244
Ch Despotis DK, Smirlis YG (2002) Data envelopment analysis with imprecise data. Eur J Oper Res 140:24–36
Charnes A, Cooper WW (1962) Programming with linear fractional functionals. Nav Res Logist Q 9:67–88
Charnes A, Cooper WW, Rhodes E (1978) Measuring efficiency of decision making units. Eur J Oper Res 2:429–444
Chen Y-C, Chiu Y-H, Huang C-W, Tu CH (2013) The analysis of bank business performance and market riskXApplying fuzzy DEA. Econ Model 32:225–232
Delgado M, Verdegay JL, Vila MA (1987) Imprecise costs in mathematical programming problems. Control Cybern 16(2):113–121
Dinu C (2008) Convex functions on time scales. Math Comp Sci Ser 35:87–96
Dubois D, Prade H (1978) Operations on fuzzy numbers. Int J Syst Sci 9(6):613–626
Hilger S (1990) Analysis on measure chains: a unified approach to continuous and discrete calculus. Results Math 18:18–56
Hu C-F, Adivar M, Fang S-C (2014) Non-L-R type fuzzy parameters in mathematical programming problems. IEEE Trans Fuzzy Syst 22:1062–1073
Inuiguchi M, Tanino T (2002) Possibilistic linear programming with fuzzy if-then rule coefficients. Fuzzy Optim Decis Mak 1:65–91
Kao C, Liu S-T (2000) Data envelopment analysis with missing data: an application to university libraries in Taiwan. J Oper Res Soc 51:897–905
Lertworasirikul S, Fang S-C, Nuttle HLW, Joines JA (2003) Fuzzy BCC model for data envelopment analysism. Fuzzy Optim Decis Mak 2:337–358
Liu B (2002) Toward fuzzy optimization without mathematical ambiguity. Fuzzy Optim Decis Mak 1:43–63
Saati SM, Memariani A, Jahanshahloo GR (2002) Efficiency analysis and ranking of DMUs with fuzzy data. Fuzzy Optim Decis Mak 3:255–267
Sarikaya MZ, Aktan N, Yildirim H (2009) Directional \(\bigtriangledown \)-derivative and curves on n-dimensional time scales. Acta Appl Math 105:45–63
Sarikaya MZ, Aktan N, Yildirim H (2009) Partial \(\bigtriangleup \)-diferentiation for multivariable functions on n-dimensional time scales. J Math Inequal 3:277–291
Sengupta JK (1992) A fuzzy systems approach in data envelopment analysis. Comput Math Appl 24(8–9):259–266
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The author would like to thank referees for their very constructive comments in revising this paper.
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Communicated by V. Loia.
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Hu, CF., Liu, FB. Data envelopment analysis with non-L-R type fuzzy data. Soft Comput 21, 5851–5857 (2017). https://doi.org/10.1007/s00500-016-2167-1
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DOI: https://doi.org/10.1007/s00500-016-2167-1