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.
Accepté le :
DOI : 10.1051/ro/2018015
Mots-clés : Data envelopment analysis, efficiency, fuzzy data, integer values
@article{RO_2018__52_4-5_1429_0, author = {Kordrostami, Sohrab and Amirteimoori, Alireza and Noveiri, Monireh Jahani Sayyad}, title = {Fuzzy integer-valued data envelopment analysis}, journal = {RAIRO - Operations Research - Recherche Op\'erationnelle}, pages = {1429--1444}, publisher = {EDP-Sciences}, volume = {52}, number = {4-5}, year = {2018}, doi = {10.1051/ro/2018015}, zbl = {1411.90226}, mrnumber = {3884155}, language = {en}, url = {http://www.numdam.org/articles/10.1051/ro/2018015/} }
TY - JOUR AU - Kordrostami, Sohrab AU - Amirteimoori, Alireza AU - Noveiri, Monireh Jahani Sayyad TI - Fuzzy integer-valued data envelopment analysis JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2018 SP - 1429 EP - 1444 VL - 52 IS - 4-5 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2018015/ DO - 10.1051/ro/2018015 LA - en ID - RO_2018__52_4-5_1429_0 ER -
%0 Journal Article %A Kordrostami, Sohrab %A Amirteimoori, Alireza %A Noveiri, Monireh Jahani Sayyad %T Fuzzy integer-valued data envelopment analysis %J RAIRO - Operations Research - Recherche Opérationnelle %D 2018 %P 1429-1444 %V 52 %N 4-5 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2018015/ %R 10.1051/ro/2018015 %G en %F RO_2018__52_4-5_1429_0
Kordrostami, Sohrab; Amirteimoori, Alireza; Noveiri, Monireh Jahani Sayyad. Fuzzy integer-valued data envelopment analysis. RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 4-5, pp. 1429-1444. doi : 10.1051/ro/2018015. http://www.numdam.org/articles/10.1051/ro/2018015/
[1] An integrated fuzzy simulation-fuzzy data envelopment analysis algorithm for job-shop layout optimization: the case of injection process with ambiguous data. Eur. J. Oper. Res. 214 (2011) 768–779. | DOI | MR | Zbl
, , and ,[2] A flexible neural network fuzzy data envelopment analysis approach for location optimization of solar plants with uncertainty and complexity. Renew. Energy 36 (2011) 3394–3401. | DOI
, and ,[3] How different are ranking methods for fuzzy numbers? A numerical study. Int. J. Approx. Reason. 54 (2013) 627–639. | DOI | MR | Zbl
and ,[4] Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2 (1978) 429–444. | DOI | MR | Zbl
, and ,[5] A cross-efficiency fuzzy data envelopment analysis technique for performance evaluation of decision making units under uncertainty. Comput. Ind. Eng. 79 (2015) 103–114. | DOI
, , and ,[6] Column generation with free replicability in DEA. Omega 37 (2009) 943–950. | DOI
and ,[7] Performance Measurement With Fuzzy Data Envelopment Analysis. Vol. 309 of Studies in Fuzzinessand Soft Computing. Springer-Verlag (2014). | DOI
and ,[8] A fuzzy expected value approach under generalized data envelopment analysis. Knowl. Based Syst. 89 (2015) 148–159. | DOI
, , , and ,[9] Fuzzy DEA: a perceptual evaluation method. Fuzzy Sets Syst. 119 (2001) 149–160. | DOI | MR
and ,[10] Self-organizing fuzzy aggregation models to rank the objects with multiple attributes. IEEE Trans. Syst. Man Cybern. Part A: Syst. Hum. 30 (2000) 573–580. | DOI
, and ,[11] A taxonomy and review of the fuzzy DEA literature: two decades in the making. Eur. J. Oper. Res. 214 (2011) 457–472. | DOI | MR | Zbl
, and ,[12] A fully fuzzified data envelopment analysis model. Int. J. Inf. Decis. Sci. 3 (2011) 252–264.
, and ,[13] Approaching fuzzy integer linear programming problems, in Interactive Fuzzy Optimization, edited by , and . Springer-Verlag, Berlin (1991). | DOI | Zbl
and ,[14] Three models of fuzzy integer linear programming. Eur. J. Oper. Res. 83 (1995) 581–593. | DOI | Zbl
and ,[15] A technical note on “A note on integer-valued radial model in DEA”. Comput. Ind. Eng. 87 (2015) 308–310. | DOI
, and ,[16] Data envelopment analysis using fuzzy concept, 28th IEEE International Symposium on Multiple-Valued Logic, May 1998(1998) 338–343.
, ,[17] A mathematical programming approach to fuzzy efficiency ranking. Int. J. Prod. Econ. 86 (2003) 145–154. | DOI
and ,[18] An integer-valued data envelopment analysis model with bounded outputs. Int. Trans. Oper. Res. 18 (2011) 741–749. | DOI | MR | Zbl
and ,[19] Theory of integer-valued data envelopment analysis under alternative returns to scale axioms. Omega 37 (2009) 988–995. | DOI
and ,[20] A note on integer-valued radial model in DEA. Comput. Ind. Eng. 66 (2013) 199–200. | DOI
, and ,[21] Evaluating the efficiency and classifying the fuzzy data: a DEA-based approach. Int. J. Ind. Math. 6 (2014) 321–327.
, and ,[22] Theory of integer-valued data envelopment analysis. Eur. J. Oper. Res. 192 (2009) 658–667. | DOI | MR | Zbl
and[23] Fuzzy Mathematical Programming. Springer-Verlag, NY (1992). | DOI | MR | Zbl
and ,[24] A new approach to some possibilistic linear programming problems. Fuzzy Sets Syst. 49 (1992) 121–133. | DOI | MR
and ,[25] A fuzzy mathematical programming approach to the assessment of efficiency with DEA models. Fuzzy Sets Syst. 139 (2003) 407–419. | DOI | MR | Zbl
, , and ,[26] Fuzzy data envelopment analysis (DEA): a possibility approach. Fuzzy Sets Syst. 139 (2003) 379–394. | DOI | MR | Zbl
, , and ,[27] Data envelopment analysis of integer-valued inputs and outputs. Comput. Oper. Res. 33 (2006) 3004–3014. | DOI | MR | Zbl
and ,[28] Fuzzy data envelopment analysis approach based on sample decision making units. J. Syst. Eng. Electron. 23 (2012) 399–407. | DOI
and ,[29] A concept of fuzzy input mix-efficiency in fuzzy DEA and its application in banking sector. Expert Syst. Appl. 40 (2013) 1437–1450. | DOI
and ,[30] A new data envelopment analysis model with fuzzy random inputs and outputs. J. Appl. Math. Comput. 33 (2010) 327–356. | DOI | MR | Zbl
and ,[31] Modeling fuzzy data envelopment analysis by parametric programming method. Expert Syst. Appl. 38 (2011) 8648–8663. | DOI
, and ,[32] A fuzzy systems approach in data envelopment analysis. Comput. Math. Appl. 24 (1992) 259–266. | MR | Zbl
,[33] Measuring efficiency by a fuzzy statistical approach. Fuzzy Sets Syst. 46 (1992) 73–80. | DOI
,[34] Establishing the existence of a distance-based upper bound for a fuzzy DEA model using duality. Chaos Solitons Fractals 41 (2009) 485–490. | DOI | Zbl
,[35] On FDH efficiency analysis: Some methodological issues and applications to retail banking, courts, and urban transit. J. Prod. Anal. 4 (1993) 183–210. | DOI
,[36] A Course in Fuzzy Systems and Control. Prentice-Hall, London, UK (1997). | Zbl
,[37] Fuzzy data envelopment analysis: a fuzzy expected value approach. Expert Syst. Appl. 38 (2011) 11678–11685. | DOI
and ,[38] Fuzzy integers and methods of constructing them to represent uncertain or imprecise integer information. Int. J. Innov. Comput. Inf. 11 (2015) 1483–1494.
, and ,[39] Fuzzy data envelopment analysis (DEA): Model and ranking method. J. Comput. Appl. Math. 223 (2009) 872–878. | DOI | Zbl
and ,[40] Ranking fuzzy subsets over the unit interval, in Proc. of 17th IEEE International Conference on Decision and Control, San Diego, CA (1979) 1435–1437. | Zbl
,[41] A procedure for ordering fuzzy subsets of the unit interval. Inf. Sci. 24 (1981) 143–161. | DOI | MR | Zbl
,[42] Aggregating preference ranking with fuzzy data envelopment analysis. Knowl. Based Syst. 23 (2010) 512–519. | DOI
, , andCité par Sources :