Data Envelopment Analysis with Indices of Time Dependent

Authors

  • Saeid Abbassbandy Department of Mathematics, Science & Research Branch, Imam Khomeini international University, Ghazvin, Iran. https://orcid.org/0000-0003-3385-4152
  • Nima Hashemi Germezi * Department of Industrial Engineering , Science & Research Branch, Islamic Azad University, Tehran, Iran.

https://doi.org/10.22105/raise.v1i4.65

Abstract

Traditional Data Envelopment Analysis (DEA) models deal with measurements of relative efficiency of  Decision Maker Unit (DMU) regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of variable indices. In this paper the indices are supposed as variables with respect to time and we present methods to estimate efficiency and ranking of DMUs.

Keywords:

Data envelopment analysis, Decision maker unit

References

  1. [1] Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
  2. [2] 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. https://doi.org/10.1287/mnsc.30.9.1078
  3. [3] Seiford, L. M., & Zhu, J. (1999). Infeasibility of super-efficiency data envelopment analysis models. INFOR: Information systems and operational research, 37(2), 174–187. https://doi.org/10.1080/03155986.1999.11732379
  4. [4] Cooper, W. W., Seiford, L. M., & Tone, K. (2007). The basic CCR model. Data envelopment analysis: A comprehensive text with models, applications, references and dea-solver software, 21–39. https://doi.org/10.1007/978-0-387-45283-8_2
  5. [5] Opricović, S., & Tzeng, G. H. (2008). A comparative analysis of the DEA-CCR model and the VIKOR method. Yugoslav journal of operations research, 18(2), 187–203. https://doi.org/10.2298/YJOR0802187O
  6. [6] Mustafa, A., Ghadiri, M., Tajaddini, A., & others. (2015). Relationship between efficiency in the traditional data envelopment analysis and possibility sets. Computers & industrial engineering, 81, 140–146. https://doi.org/10.1016/j.cie.2015.01.001
  7. [7] Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management science, 39(10), 1261–1264. https://doi.org/10.1287/mnsc.39.10.1261
  8. [8] Mehrabian, S., Alirezaee, M. R., & Jahanshahloo, G. R. (1999). A complete efficiency ranking of decision making units in data envelopment analysis. Computational optimization and applications, 14(2), 261-266. https://doi.org/10.1023/A:1008703501682
  9. [9] Sexton, T. R., Silkman, R. H., & Hogan, A. J. (1986). Data envelopment analysis: Critique and extensions. New directions for program evaluation, 1986(32), 73–105. https://doi.org/10.1002/ev.1441
  10. [10] Adler, N., Friedman, L., & Sinuany-Stern, Z. (2002). Review of ranking methods in the data envelopment analysis context. European journal of operational research, 140(2), 249–265. https://doi.org/10.1016/S0377-2217(02)00068-1
  11. [11] Jahanshahloo, G. R., Lotfi, F. H., Rezai, H. Z., & Balf, F. R. (2005). Using Monte Carlo method for ranking efficient DMUs. Applied mathematics and computation, 162(1), 371–379. https://doi.org/10.1016/j.amc.2003.12.139

Downloads

Published

2024-10-19

Issue

Vol. 1 No. 4 (2024): Research Annals of Industrial and Systems Engineering

Section

Articles

How to Cite

Abbassbandy, S. ., & Hashemi Germezi, N. . (2024). Data Envelopment Analysis with Indices of Time Dependent. Research Annals of Industrial and Systems Engineering, 1(4), 262-275. https://doi.org/10.22105/raise.v1i4.65

Similar Articles

1-10 of 36

You may also start an advanced similarity search for this article.