Fuzzy Systems and its Applications

Fuzzy Systems and its Applications

Management of uncertainty in DEA using intuitive fuzzy and fuzzy rough parameters

Document Type : Original Article

Authors
Amir Rahimi 1
Hassan mishmast 1
Faranak H. Saljooghi 2
1 Department of Mathematics, University of Sistan and Baluchestan, Zahedan, Iran
2 University of Sistan and Baluchestan
10.22034/jfsa.2024.467659.1233
Abstract
This article examines the impact of uncertainty in the form of intuitionistic fuzzy data and rough fuzzy parameters on performance evaluation and management using Data Envelopment Analysis (DEA). The primary objective of this research is to enhance the accuracy and management of uncertainty in DEA models. In the present study, we utilize intuitionistic fuzzy imprecise data, each parameter of which forms a rough fuzzy set. The expected values of intuitionistic fuzzy and rough fuzzy parameters play a significant role in this research. Given that rough fuzzy parameters help the model to work more effectively with imprecise and uncertain data, and intuitionistic fuzzy data provide more information and details about variations and uncertainties, the combination of these two concepts allows DEA models to assess and analyze the performance of various units with greater accuracy and confidence, leading to improved management of uncertainties. However, the increased model size and computational complexity are considered limitations of this approach. We illustrate the proposed approach with a numerical example. The use of the results from the proposed models can be an effective tool in performance evaluation across various organizations and industries, leading to significant improvements in decision-making processes.
Keywords
Data Envelopment Analysis
intuitive fuzzy
fuzzy rough
Expected value interval
Subjects
[1]    Atanassov, K. (1986) Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20, 87-96.
[2]    Sahil, M., A., & Lohani, D. (2024) Comprehensive intuitionistic fuzzy network data envelopment analysis incorporating undesirable outputs and shared resources, Methods X,, 12, https://doi.org/10.1016/j.mex.2024.102710.
[3]    Pawlak, Z. (1982) Rough sets. International Journal of Parallel Programming, Vol. 11, pp. 341-356.
[4]    Liu, B.D. (2004) Uncertain Theory: An Introduction to its Axiomatic Foundation. Springer, Berlin.
[5]    Khanjani, R., Charles, V., and Jalalzadeh, L, (2014) Fuzzy rough DEA model: A possibility and expected value approaches. Expert Systems with Applications, 41, 434-444.
[6]    Jafarzadeh, M., Davvaz, B. (2013) Rough Intuitionistic Fuzzy Information Systems. Fuzzy Information and Engineering, 5:4, 445-458.
[7]    Rizvi, R., Naqvi, H. J., Nadeem, D., (2002) Rough Intuitionistic Fuzzy Sets. Conference: Proceedings of the 6th Joint Conference on Information Science.
[8]    Kumar, A. T., Nath, A., Kumar, R. P., Maratha, P., (2024) A novel intuitionistic fuzzy rough instance selection and attribute reduction with kernelized intuitionistic fuzzy C-means clustering to handle imbalanced datasets. Expert Systems with Applications, 251, 437 -449.
[9]    Jain, P., Tiwari, A. & Som, T. (2024) Intuitionistic fuzzy rough set model based on k-means and its application to enhance prediction of aptamer-protein interacting pairs. J Ambient Intell Human Comput, 15, 3575-3586.
[10]        Noorjahan S., Sharief Basha S. (2024) Developing an intuitionistic fuzzy rough new correlation coefficient approach for enhancing robotic vacuum cleaner. Science Progress. 107(3).
[11]    Burillo, P. Bustince, H. (1996) Entropy on intuitionistic fuzzy sets and on interval-valued fuzzy sets, Fuzzy Sets and Systems, 78(3), 305 - 316.
[12]        Grzegorzewski, p., (2002) Intuitionistic fuzzy numbers. Accepted for the precedingof the IFSA, 2003, world Congress.
[13]        Zadeh, L. A. (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1, 9-34.
Fuzzy Systems and its Applications
Volume 7, Issue 1 - Serial Number 14
Open Access Statement
June 2024
Pages 209-228

  • Receive Date 13 July 2024
  • Revise Date 29 September 2024
  • Accept Date 07 October 2024