A novel fuzzy non-radial data envelopment analysis: An application in transportation
RAIRO. Operations Research, Tome 55 (2021) no. 4, pp. 2189-2202

The slack-based measure (SBM) DEA model is a non-radial model used to calculate the relative efficiency, input, and output targets of the different decision-making units (DMUs) based on their best peers or efficient frontier. The conventional SBM DEA model used crisp inputs and outputs. But, it can be observed in real-life problems that sometimes the available data is in linguistic forms such as “few”, “many”, “small”, or missing data. The DEA technique is frontier based, and therefore, imprecise data may lead to untenable results. Fuzzy theory, which is already established to handle uncertain data, can overcome this problem. Furthermore, the sensitivity and stability analysis have been checked the robustness of fuzzy DEA models. In this study, sensitivity and stability analysis of the fuzzy SBM DEA has been performed. The lower and upper sensitive bounds for inputs and outputs variables have been obtained for both the inefficient and efficient DMUs to calculate the input and output targets. Finally, a real-life transportation problem for the validity of the study is presented for its depiction.

DOI : 10.1051/ro/2021097
Classification : 03B52, 90C08, 90C31, 90C70, 03E72
Keywords: Data Envelopment Analysis, fuzzy slacks-based measure model, credibility measure, decision-making units, sensitivity analysis
@article{RO_2021__55_4_2189_0,
     author = {Mahla, Deepak and Agarwal, Shivi and Mathur, Trilok},
     title = {A novel fuzzy non-radial data envelopment analysis: {An} application in transportation},
     journal = {RAIRO. Operations Research},
     pages = {2189--2202},
     year = {2021},
     publisher = {EDP-Sciences},
     volume = {55},
     number = {4},
     doi = {10.1051/ro/2021097},
     mrnumber = {4284910},
     language = {en},
     url = {https://www.numdam.org/articles/10.1051/ro/2021097/}
}
TY  - JOUR
AU  - Mahla, Deepak
AU  - Agarwal, Shivi
AU  - Mathur, Trilok
TI  - A novel fuzzy non-radial data envelopment analysis: An application in transportation
JO  - RAIRO. Operations Research
PY  - 2021
SP  - 2189
EP  - 2202
VL  - 55
IS  - 4
PB  - EDP-Sciences
UR  - https://www.numdam.org/articles/10.1051/ro/2021097/
DO  - 10.1051/ro/2021097
LA  - en
ID  - RO_2021__55_4_2189_0
ER  - 
%0 Journal Article
%A Mahla, Deepak
%A Agarwal, Shivi
%A Mathur, Trilok
%T A novel fuzzy non-radial data envelopment analysis: An application in transportation
%J RAIRO. Operations Research
%D 2021
%P 2189-2202
%V 55
%N 4
%I EDP-Sciences
%U https://www.numdam.org/articles/10.1051/ro/2021097/
%R 10.1051/ro/2021097
%G en
%F RO_2021__55_4_2189_0
Mahla, Deepak; Agarwal, Shivi; Mathur, Trilok. A novel fuzzy non-radial data envelopment analysis: An application in transportation. RAIRO. Operations Research, Tome 55 (2021) no. 4, pp. 2189-2202. doi: 10.1051/ro/2021097

[1] S. Agarwal, Efficiency measure by fuzzy data envelopment analysis model. Fuzzy Inf. Eng. 1 6 (2014) 59–70. | MR | DOI

[2] S. Agarwal, SBM data envelopment analysis in fuzzy environment. Math. Sci. Int. Res. J. 3 (2014) 478–484.

[3] S. Agarwal, Fuzzy slack based measure of data envelopment analysis: a possibility approach. In: Proceedings of the Third International Conference on Soft Computing for Problem Solving (2014) 733–740. | DOI

[4] S. Agarwal, S. P. Yadav and S. P. Singh, DEA based estimation of the technical efficiency of state transport undertakings in India. Opsearch 47 (2010) 216–230. | DOI

[5] M. Arana-Jiménez, M. C. Sánchez-Gil and S. Lozano, A fuzzy DEA slacks-based approach. J. Comput. Appl. Math. (2020) 113180. | MR

[6] M. Arana-Jimenez, M. C. Sánchez-Gil and S. Lozano, Efficiency assessment and target setting using a fully fuzzy DEA approach. Int. J. Fuzzy Syst. 22 (2020) 1056–1072. | DOI

[7] R. D. Banker, Maximum likelihood, consistency and DEA statistical foundations. Manage. Sci. 39 (1993) 1265–1273. | Zbl | DOI

[8] A. Charnes and W. W. Cooper, Chance-constrained programming. Manage. Sci. 6 (1959) 73–79. | MR | Zbl | DOI

[9] A. Charnes and L. Neralić, Sensitivity analysis of the additive model in data envelopment analysis. Eur. J. Oper. Res. 48 (1990) 332–341. | Zbl | DOI

[10] A. Charnes, W. W. Cooper and E. Rhodes, Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2 (1978) 429–444. | MR | Zbl | DOI

[11] A. Charnes, W. W. Cooper, B. Golany, L. Seiford and J. Stutz, Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. J. Econometrics 30 (1985) 91–107. | MR | Zbl | DOI

[12] W. W. Cooper, L. M. Seiford and K. Tone, Data envelopment analysis. In: Handbook on Data Envelopment Analysis (2000) 1–40.

[13] A. Emrouznejad and A. Mustafa, Fuzzy data envelopment analysis: a discrete approach. Expert Syst. App. 39 (2012) 2263–2269. | DOI

[14] A. Emrouznejad and M. Tavana, Performance Measurement with Fuzzy Data Envelopment Analysis. Springer (2014). | DOI

[15] A. Emrouznejad and G. L. Yang, A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Soc.-Econ. Planning Sci. 61 (2018) 4–8. | DOI

[16] P. Guo and H. Tanaka, Fuzzy DEA: a perceptual evaluation method. Fuzzy Sets Syst. 119 (2001) 149–160. | MR | DOI

[17] P. Gupta, M. K. Mehlawat, A. Kumar, S. Yadav and A. Aggarwal, A credibilistic fuzzy DEA approach for portfolio efficiency evaluation and rebalancing toward benchmark portfolios using positive and negative returns. Int. J. Fuzzy Syst. 22 (2020) 824–843. | DOI

[18] C. Heydari, H. Omrani and R. Taghizadeh, A fully fuzzy network DEA-Range Adjusted Measure model for evaluating airlines efficiency: a case of Iran. J. Air Transp. Manage. 89 (2020) 101923. | DOI

[19] G. R. Jahanshahloo, M. Soleimani-Damaneh and E. Nasrabadi, Measure of efficiency in DEA with fuzzy input–output levels: a methodology for assessing, ranking and imposing of weights restrictions. Appl. Math. Comput. 156 (2004) 175–187. | MR | Zbl

[20] G. R. Jahanshahloo, F. Hosseinzadeh, N. Shoja, M. Sanei and G. Tohidi, Sensitivity and stability analysis in DEA. Appl. Math. Comput. 169 (2005) 897–904. | MR | Zbl

[21] D. Kahneman and A. Tversky, Prospect theory: an analysis of decision under risk. Econometrics 47 (1979) 263–291. | MR | Zbl | DOI

[22] C. Kao and S. T. Liu, Fuzzy efficiency measures in data envelopment analysis. Fuzzy Sets Syst. 113 (2000) 427–437. | Zbl | DOI

[23] M. Z. A. Langroudi, A. Emrouznejad, A. Mustafa and J. Ignatius, Type-2 TOPSIS: a group decision problem when ideal values are not extreme endpoints. Group Decision Negotiation 22 (2013) 851–866. | DOI

[24] S. Lertworasirikul, S. C. Fang, J. A. Joines and H. L. Nuttle, Fuzzy data envelopment analysis (DEA): a possibility approach. Fuzzy Sets Syst. 139 (2003) 379–394. | MR | Zbl | DOI

[25] S. Lertworasirikul, S. C. Fang, J. Joines and H. Nuttle, Fuzzy data envelopment analysis: a credibility approach. Fuzzy Sets Based Heuristics Optim. (2003) 141–158. | MR | Zbl | DOI

[26] B. Liu, Uncertainty Theory. Springer, Berlin, Heidelberg (2007) 205–234. | MR | Zbl | DOI

[27] B. Liu, Some research problems in uncertainty theory. J. Uncertain Syst. 3 (2009) 3–10.

[28] B. Liu, Uncertainty Theory. Springer, Berlin, Heidelberg (2010) 1–79. | MR | Zbl

[29] B. Liu and Y. K. Liu, Expected value of fuzzy variable and fuzzy expected value models. IEEE Trans. Fuzzy Syst. 10 (2002) 445–450. | DOI

[30] F. H. Lotfi, M. A. Jondabeh and M. Faizrahnemoon, Senstivity analysis in fuzzy environment. Appl. Math. Sci. 4 (2010) 1635–1646. | MR | Zbl

[31] C. K. Lovell, Measuring the macroeconomic performance of the Taiwanese economy. Int. J. Prod. Econ. 39 (1995) 165–178. | DOI

[32] D. Mahla, S. Agarwal, A credibility approach on fuzzy Slacks-Based Measure (SBM) model (2020). DOI: (In Press). | DOI | MR

[33] R. Mahmoudi, A. Emrouznejad, S. N. Shetab-Boushehri and S. R. Hejazi, The origins, development and future directions of data envelopment analysis approach in transportation systems. Soc.-Econ. Plann. Sci. 69 (2020) 100672. | DOI

[34] L. Neralić and R. E. Wendell, Sensitivity in data envelopment analysis using an approximate inverse matrix. J. Oper. Res. Soc. 55 (2004) 1187–1193. | Zbl | DOI

[35] L. Neralić and R. E. Wendell, Enlarging the radius of stability and stability regions in Data Envelopment Analysis. Eur. J. Oper. Res. 278 (2019) 430–441. | MR | DOI

[36] O. B. Olesen and N. C. Petersen, Chance constrained efficiency evaluation. Manage. Sci. 41 (1995) 442–457. | Zbl | DOI

[37] S. Saati and A. Memariani, SBM model with fuzzy input-output levels in DEA. Aust. J. Basic Appl. Sci. 3 (2009) 352–357.

[38] M. Sanei, N. Noori and H. Saleh, Sensitivity analysis with fuzzy data in DEA. Appl. Math. Sci. 3 (2009) 1235–1241. | MR

[39] L. M. Seiford and J. Zhu, Sensitivity and stability of the classifications of returns to scale in data envelopment analysis. J. Prod. Anal. 12 (1999) 55–75. | DOI

[40] J. K. Sengupta, Efficiency measurement in stochastic input-output systems. Int. J. Syst. Sci. 13 (1982) 273–287. | MR | Zbl | DOI

[41] P. Smith, Model misspecification in data envelopment analysis. Ann. Oper. Res. 73 (1997) 233–252. | Zbl | DOI

[42] K. Tone, A slacks-based measure of efficiency in data envelopment analysis. Eur. J. Oper. Res. 130 (2001) 498–509. | MR | Zbl | DOI

[43] P. Wanke, C. P. Barros and A. Emrouznejad, A comparison between stochastic DEA and fuzzy DEA approaches: revisiting efficiency in Angolan banks. RAIRO:OR 52 (2018) 285–303. | MR | Zbl | Numdam | DOI

[44] M. Wen, C. You and R. Kang, A new ranking method to fuzzy data envelopment analysis. Comput. Math. App. 59 (2010) 3398–3404. | MR | Zbl

[45] M. Wen, Z. Qin and R. Kang, Sensitivity and stability analysis in fuzzy data envelopment analysis. Fuzzy Optim. Decis. Making 10 (2011) 1–10. | Zbl | DOI

[46] M. Wen, Z. Qin, R. Kang and Y. Yang, Sensitivity and stability analysis of the additive model in uncertain data envelopment analysis. Soft Comput. 19 (2015) 1987–1996. | DOI

[47] L. A. Zadeh, Fuzzy sets. Inf. Control 8 (1965) 338–353. | MR | Zbl | DOI

[48] M. Zahedi-Seresht, G. R. Jahanshahloo and J. Jablonsky, A robust data envelopment analysis model with different scenarios. Appl. Math. Modell. 52 (2017) 306–319. | MR | DOI

[49] Z. Zhou, E. Chen, H. Xiao, T. Ren and Q. Jin, Performance evaluation of portfolios with fuzzy returns. RAIRO:OR 53 (2019) 1581–1600. | MR | Zbl | Numdam | DOI

Cité par Sources :