CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Ranking Decision making units using Fuzzy Multi-Objective Approach

by Hegazy M. Zaher, Ramadan A. Zeineldin, Gamil M. Abdelshafy
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 126 - Number 2
Year of Publication: 2015
Authors: Hegazy M. Zaher, Ramadan A. Zeineldin, Gamil M. Abdelshafy
10.5120/ijca2015905985

Hegazy M. Zaher, Ramadan A. Zeineldin, Gamil M. Abdelshafy . Ranking Decision making units using Fuzzy Multi-Objective Approach. International Journal of Computer Applications. 126, 2 ( September 2015), 1-6. DOI=10.5120/ijca2015905985

@article{ 10.5120/ijca2015905985,
author = { Hegazy M. Zaher, Ramadan A. Zeineldin, Gamil M. Abdelshafy },
title = { Ranking Decision making units using Fuzzy Multi-Objective Approach },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 126 },
number = { 2 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume126/number2/22521-2015905985/ },
doi = { 10.5120/ijca2015905985 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:16:22.035707+05:30
%A Hegazy M. Zaher
%A Ramadan A. Zeineldin
%A Gamil M. Abdelshafy
%T Ranking Decision making units using Fuzzy Multi-Objective Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 126
%N 2
%P 1-6
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents Data Envelopment Analysis (DEA) has been used in a wide variety of applied research and it is a linear programming methodology that has been widely used to evaluate the performance of a set of decision-making units (DMUs). It requires crisp input and output data. However, in reality input and output cannot be measured in a precise manner. Firstly using DEA to evaluate the efficient and inefficient decision-making units (DMUs) with the (CCR) model. Secondly the resulted weights for each input and output are considered as fuzzy sets and are then converted to fuzzy number. Thirdly using Fuzzy multi-objective approach to find the highest and lowest of the weighted values. Fourthly usingthe results from stage it to rank from highest to lowest. An application from banking industry is presented.

References
  1. Adler, N., Friedman, L., &Sinuany-Stern, Z. (2002). Review of ranking methods in the data envelopment analysis context. European Journal of Operational Research, 140, 249–265.
  2. Ali HoseinGharib, Mohammad SedaghatiJahromi, (2013). Evaluating Efficiency Using Fuzzy DEA By Fuzzy Constraints For Finding a Common Set of Weights. International Journal of Emerging Trends & Technology in Computer Science. ISSN 2278-6856.
  3. A. Charnes, W. W. Cooper and E. Rhodes, (1978).Measuring the efficiency of decision making units, European Journal of Operational Research, 2 429-444.
  4. Andersen, P., Petersen, N.C., (1993), A procedure for ranking efficient units in data envelopment analysis. Management Science 39 (10), 1261–1294.
  5. Adel Hatami-Marbini, Saber Saati, Madjid Tavana, (2011),An ideal-seeking fuzzy data envelopment analysis framework, European Journal of Operational Research, 1062–1070.
  6. A. Ebrahimnejad , F. HosseinzadehLotfi (2012), Equivalence relationship between the general combined-oriented CCR model and the weighted minimax MOLP formulation; Journal of King Saud University, 47–54.
  7. Abdelwaheb Rebai, (2009), A Mathematical Approach to Solve Data Envelopment Analysis Models when Data are LR Fuzzy Numbers, Applied Mathematical Sciences, Vol. 3, no. 48, 2383 – 2396.
  8. Bardhan, I., Bowlin, W. F., Cooper, W. W., &Sueyoshi, T. (1996). Model for efficiency dominance in data envelopment analysis. Part I: Additive models and MED.
  9. D. J. Aigner, C. A. K. Lovell and P. Schmidt,(1977), Formulation and estimation of stochastic frontier production models, Journal of Econometrics, 6 21-37.
  10. F. Hossainzadeh, G. R. Jahanshahloo, M. Kodabakhshi and F. Moradi (2011), A fuzzy chance constraint multi objective programming method in data envelopment analysis, African Journal of Business Management Vol. 5(32), pp. 12873-12881.
  11. Golany, B., (1988), An interactive MOLP procedure for the extension of data envelopment analysis to effectiveness analysis. Journal of the Operational Research Society 39 (8), 725–734.
  12. Luiz Biondi Neto, Carlos Correia , Lidia Angulo Meza (2011), A geometrical approach for fuzzy DEA frontiers using different T norms,World Scientific and Engineering Academy and Society (WSEAS) Stevens Point, Wisconsin, USA, 127-136.
  13. Liu B, Liu YK (2002). Expected value of fuzzy variable and fuzzy expected value models." IEEE Trans Fuzzy Syst., 10( 4): 445-450.
  14. M. J. Farrell, (1957), The measure ement of productive efficiency, Journal of the Royal Statistical Society, Series A, 120 253-290.
  15. R.D.Banker, A. Charnes, and W.W.Cooper, (1984), Some models for estimating technical and scale inefficiency in data envelopment analysis, Management Science, 30 -1078-1092.
  16. Torgersen, A. M., Forsund, F. R., &Kittelsen, S. A. C. (1996). Slack-adjusted efficiency measures and ranking of efficient units. The Journal of Productivity Analysis, 7,379–398.
  17. Sexton, T.R., Silkman, R.H., Hogan, A.J., (1986), Data envelopment analysis: Critique and extensions. In: Silkman, R.H. (Ed.), Measuring Efficiency: An Assessment of Data Envelopment Analysis. Jossey-Bass, San Francisco, CA, pp. 73– 105.
  18. Wen M, Youb C, Kana R (2010). A new ranking method to fuzzy data envelopment analysis. Comp. Math. Appl., 59: 3398-3404.
  19. Najmeh Malekmohammadi, Farhad Hossein zadeh Lotfi , Azmi B. Jaafar (2011); Target setting in data envelopment analysis using MOLP; . The Journal of the Operational Research; 328–338.
  20. Makui1, A. Alinezhad, R. KianiMavi,M. Zohreh bandian (2008), A Goal Programming Method for Finding Common Weights in DEA with an Improved Discriminating Power for Efficiency; Journal of Industrial and Systems Engineering; pp 293-303.
  21. Jian-Bo Yang, Brandon Y.H. Wong , Dong-Ling Xu , Theodor J. Stewart (2009), Integrating DEA-oriented performance assessment and target setting using interactive MOLP methods; European Journal of Operational Research 205–222.
  22. K. Sam Park , Dong Eun Shin (2012), Interactive multiobjective optimization approach to the input–output design of opening new branches; European Journal of Operational Research 220, 530–538.
  23. C. Veeramani, C. Duraisamy and A. Nagoorgani (2011), Solving Fuzzy Multi-Objective Linear Programming Problems With Linear Membership Functions; Australian Journal of Basic and Applied Sciences, 5(8): 1163-1171, 2011, ISSN 1991-8178.
  24. Majid ZerafatAngiz L., Adli Mustafa. Ali Emrouznejad (2010), Ranking efficient decision-making units in data envelopment analysis using fuzzy concept ;journal homepage: www.elsevier.com/ locate/caie, Computers & Industrial Engineering 59, 712–719.
  25. Adel Hatami-Marbini, SaberSaati, Madjid Tavana (2011), Data Envelopment Analysis with Fuzzy Parameters: An Interactive Approach. International Journal of Operations Research and Information Systems, 2(3), 39-53, July-September 2011 39.
  26. Saowanee Lertworasirikul, Shu-Cherng Fang, Jefrey A. Joines, Henry L.W. Nuttle (2003), Fuzzy data envelopment analysis (DEA): a possibility Approach, European Journal of Operational Research, 379–394.1
  27. P .Guo and H. Tanaka, (2001) Fuzzy DEA: A Perceptual evaluation method, Fuzzy sets and system, 119-149-160.
Index Terms

Computer Science
Information Sciences

Keywords

Data envelopment analysis ranking methods in DEA Multi-objective data envelopment analysis Fuzzy data envelopment analysis Fuzzy multi-objective approach.

Powered by PhDFocusTM