Submit your research to the International Journal "Notes on Intuitionistic Fuzzy Sets". Contact us at nifs.journal@gmail.com
Call for Papers for the 27th International Conference on Intuitionistic Fuzzy Sets is now open!
Conference: 5–6 July 2024, Burgas, Bulgaria • EXTENDED DEADLINE for submissions: 15 APRIL 2024.

Issue:Development of intuitionistic fuzzy cost efficiency model in data envelopment analysis

From Ifigenia, the wiki for intuitionistic fuzzy sets and generalized nets
Revision as of 15:01, 27 October 2023 by Vassia Atanassova (talk | contribs) (Created page with "{{PAGENAME}} {{PAGENAME}} {{PAGENAME}} {{issue/title | title = Development of intuitionistic fuzzy cost efficiency model in data envelopment analysis | shortcut = nifs/29/3/298-317 }} {{issue/author | author = Anjali Sonkariya | institution = Department of Mathematics, Indian Institute of Technology | a...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search
shortcut
http://ifigenia.org/wiki/issue:nifs/29/3/298-317
Title of paper: Development of intuitionistic fuzzy cost efficiency model in data envelopment analysis
Author(s):
Anjali Sonkariya
Department of Mathematics, Indian Institute of Technology, Roorkee, India
anjalisonkariya@gmail.com
Shiv Prasad Yadav
Department of Mathematics, Indian Institute of Technology, Roorkee, India
spyorfma@gmail.com
Published in: Notes on Intuitionistic Fuzzy Sets, Volume 29 (2023), Number 3, pages 292–297
DOI: https://doi.org/10.7546/nifs.2023.29.3.298-317
Download:  PDF (616  Kb, Info)
Abstract: Data envelopment analysis (DEA) is a non-parametric linear programming (LP) based technique to measure the relative efficiencies of decision-making units (DMUs). The conventional DEA models assume that input-output data is crisp, which may not always be feasible in practical situations due to the presence of ambiguity and imprecision. Therefore, to handle uncertain and imprecise data, the concept of intuitionistic fuzzy sets (IFS) has been introduced. In this study, the relative efficiencies of DMUs with uncertain data will be determined. For this reason, the conventional cost efficiency (CE) model of DEA is extended to IF environment. Also, the lower and upper-cost efficiency models are developed using $ \alpha $-cut and $ \beta $-cut approach. The data for inputs, outputs and input prices are considered intuitionistic fuzzy numbers (IFNs), in particular triangular intuitionistic fuzzy numbers (TIFNs). To demonstrate the practical application of the proposed intuitionistic fuzzy cost efficiency models (IFCEMs), a numerical example is presented.
Keywords: α- and β-cuts, Cost efficiency, Data envelopment analysis, Performance measurement, Intuitionistic fuzzy set.
AMS Classification: 03E72.
References:
  1. Aghayi, N. (2017). Cost efficiency measurement with fuzzy data in DEA. Journal of Intelligent & Fuzzy Systems, 32, 409–420.
  2. Arya, A., & Yadav, S. (2018). Development of intuitionistic fuzzy integrated superefficiency SBM model. Notes on Intuitionistic Fuzzy Sets, 24(1), 131–140.
  3. Arya, A., & Yadav, S. (2019). Development of intuitionistic fuzzy data envelopment analysis models and intuitionistic fuzzy input–output targets. Soft Computing, 23, 8975–8993.
  4. Atanassov, K. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96.
  5. Bagherzadeh Valami, H. (2009). Cost efficiency with triangular fuzzy number input prices: An application of DEA. Chaos, Solitons & Fractals, 42, 1631–1637.
  6. Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092.
  7. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.
  8. Farrell, M. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120, 253–281.
  9. Jahanshahloo, G., Hosseinzadeh Lotfi, F., Alimardani Jondabeh, M., Banihashemi, S., & Lakzaie, L. (2008). Cost efficiency measurement with certain price on fuzzy data and application in insurance organization. Applied Mathematical Sciences, 2(1), 1–18.
  10. Kao, C., & Liu, S. (2000). Fuzzy efficiency measures in data envelopment analysis. Fuzzy Sets and Systems, 113, 427–437.
  11. Pourmahmoud, J., & Sharak, N. (2020). Evaluating cost efficiency using fuzzy Data Envelopment Analysis method. Iranian Journal of Operations Research, 11, 25–42.
  12. Puri, J., & Yadav, S. (2016). A fully fuzzy DEA approach for cost and revenue efficiency measurements in the presence of undesirable outputs and its application to the banking sector in India. International Journal of Fuzzy Systems, 18, 212–226.
  13. Sarab, R., Amirteimoori, A., Malek, A., & Kordrostami, S. (2021). Cost efficiency analysis in data envelopment analysis framework: An application to sugar industries. Journal of Information and Optimization Sciences, 42(5), 1137–1161.
  14. Tone, K. (2002). A strange case of the cost and allocative efficiencies in DEA. Journal of the Operational Research Society, 53, 1225–1231.
  15. Venkatesh, A., & Kushwaha, S. (2018). Short and long-run cost efficiency in Indian public bus companies using Data Envelopment Analysis. Socio-Economic Planning Sciences, 61, 29–36.
  16. Zadeh, L. (1965). Fuzzy sets. Information and Control, 8, 338–353.
Citations:

The list of publications, citing this article may be empty or incomplete. If you can provide relevant data, please, write on the talk page.

Retrieved from "https://ifigenia.org/index.php?title=Issue:Development_of_intuitionistic_fuzzy_cost_efficiency_model_in_data_envelopment_analysis&oldid=11706"