Introducing a New Method to Expand TOPSIS Decision Making Model to Fuzzy TOPSIS

Volume 2, Issue 1, pp 150--159 http://dx.doi.org/10.22436/jmcs.002.01.16

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Authors

Ali Mohammadi - Isalamic Azad University-Bojnourd Branch Abolfazl Mohammadi - Chemical Engineering Phd Student, Engineering College of Tarbiat Modares University, Tehran, Iran Hossain Aryaeefar - Industrail Engineering B.S.c Student, Engineering Faculty of Bojnourd University

Abstract

Fuzzy TOPSIS is one of the various models of multiple attributes decision making with fuzzy values that so far diverse models have been introduced for it. In this paper, according to these models, a new method is presented for fuzzy TOPSIS with triangular fuzzy data. So, it has better and more accurate outputs in comparison with previous methods. At last, we solve a fuzzy multiple attributes decision making problem to demonstrate the proposed method.

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Keywords

• fuzzy TOPSIS
• fuzzy number
• linguistic variables
• triangular fuzzy number.

MSC

•  90B50
•  90C70
•  03E72
•  91F20

References

• [1] M. J. Asgharpour, Multi indicator decision making, Tehran University Publishment, Tehran (1999)
  • Google Scholar


• [2] C. T. Chen, Extensions of the TOPSIS for group decision‐making under fuzzy environment, Fuzzy Sets and Systems, 114 (2000), 1--9
  • View Article
  • Google Scholar
  • MATH


• [3] H. Deng, C. H. Yeh, R. J. Willis, Inter‐company comparison using modified TOPSIS with objective weights, Computers & Operations Research, 27 (2000), 963--973
  • View Article
  • Google Scholar
  • MATH


• [4] T. C. Chu, Selecting plant location via a fuzzy TOPSIS approach, The International Journal of Advanced Manufacturing Technology, 20 (2002), 859--864
  • View Article
  • Google Scholar


• [5] T. C. Chu, Selecting plant location via a fuzzy TOPSIS approach, The International Journal of Advanced Manufacturing Technology, 20 (2002), 859--864
  • View Article
  • Google Scholar


• [6] T. C. Chu, Facility location selection using fuzzy TOPSIS under group decisions, Internat. J. Uncertain. Fuzziness Knowledge-Based Systems, 10 (2002), 687--701
  • View Article
  • MathSciNet
  • Google Scholar
  • MATH


• [7] M. A. Abo-Sinna, A. H. Amer, Extensions of TOPSIS for multi objective large‐scale nonlinear programming problems, Appl. Math. Comput., 162 (2005), 243--256
  • View Article
  • MathSciNet
  • Google Scholar
  • MATH


• [8] M. A. Abo-Sinna, A. H. Amer, Extensions of TOPSIS for multi‐objective large‐scale nonlinear programming problems, Appl. Math. Comput., 162 (2005), 243--256
  • View Article
  • MathSciNet
  • Google Scholar
  • MATH


• [9] S. Saghafian, S. R. Hejazi, Multi-Criteria Group Decision Making a Modified Fuzzy TOPSIS Procedure, Web Technologies and Internet Commerce, 2 (2005), 215--221
  • View Article
  • Google Scholar


• [10] G. R. Jahanshahloo, F. H. Lotfi, M. Izadikhah, An algorithmic method to extend TOPSIS method for decision making problems with interval data, Appl. Math. Comput., 175 (2006), 1375--1384
  • View Article
  • Google Scholar
  • MATH


• [11] G. R. Jahanshahloo, F. H. Lotfi, M. Izadikhah, Extension of the TOPSIS method for decision‐making problems with fuzzy data, Appl. Math. Comput., 181 (2006), 1544--1551
  • View Article
  • Google Scholar
  • MATH


• [12] H.-S. Shih, H.-J. Shyur, E. S. Lee, An Extension of TOPSIS for Group Decision Making, Math. Comput. Modelling, 45 (2007), 801--813
  • View Article
  • Google Scholar
  • MATH


• [13] Y. J. Wang, H. S. Lee, Generalizing TOPSIS for fuzzy multiple‐criteria group decision‐making, Comput. Math. Appl., 53 (2007), 1762--1772
  • View Article
  • MathSciNet
  • Google Scholar
  • MATH


• [14] T. Y. Chen, C. Y. Tsao, The interval‐valued fuzzy TOPSIS method and experimental analysis, Fuzzy Sets and Systems, 159 (2008), 1410--1428
  • View Article
  • MathSciNet
  • Google Scholar
  • MATH


• [15] T. C. Chu, Y. C. Lin, A Fuzzy TOPSIS Method for Robot Selection, Int. J. Adv. Manuf. Technol., 21 (2003), 284--290
  • View Article
  • Google Scholar


• [16] J. H. Park, I. Y. Park, Y. C. Kwun, X. Tan, Extension of the TOPSIS method for decision making problems under interval‐valued intuitionist fuzzy environment, Appl. Math. Model., 35 (2011), 2544--2556
  • View Article
  • Google Scholar


• [17] G. A. A. Ahmadi, M. J. Taghipourian, Y. Taghipourian, The evaluation of instructors TRAINING Performance by fuzzy MCDM, Proceedings of the 2nd International Conference of Teaching and Learning (INTI University College, Malaysia), 2009 (2009), pages
  • View Article
  • Google Scholar


• [18] İ. Ertuğrul, N. Karakaşoğlu, Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods, Expert Syst. Appl., 36 (2007), 702--715
  • View Article
  • Google Scholar


• [19] Y. M. Wang, T. M. S. Elhag, Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment, Expert Syst. Appl., 31 (2006), 309--319
  • View Article
  • Google Scholar


• [20] Y. J. Wang, Applying FMCDM to evaluate financial performance of domestic airlines in Taiwan, Expert Syst. Appl., 34 (2008), 1837--1845
  • View Article
  • Google Scholar


• [21] J. W. Wang, C. H. Cheng, K. C. Huang, Fuzzy hierarchical TOPSIS for supplier selection, Applied Soft Computing, 9 (2009), 377--386
  • View Article
  • Google Scholar


• [22] F. E. Boran, S. Genç, M. Kurt, D. Akay, A multi‐criteria intuitionist fuzzy group decision making for supplier selection with TOPSIS method, Expert Syst. Appl., 36 (2009), 11363--11368
  • View Article
  • Google Scholar


• [23] J. J. Color, U. S. Color, B. Uann, Fuzzy sets theory, principles and yields, Amirkabir University Press, Tehran (2005)
  • Google Scholar


• [24] M. Nurani, Fuzzy numbers and their comparing methods, A.M. thesis (Kerman University), Kerman (1999)
  • Google Scholar


• [25] H. J. Zimmennann, Fuzzy Set Theory and its Applications, Kluwer Academic Publishers, London (1991)
  • Google Scholar


• [26] A. Mohammadi, J. Shohani, H. Jahanshahi, Numerical taxonomy analysis with triangular fuzzy data, The 10th conference of fuzzy systems (Iran, Shahid Beheshti University), 2010 (2010), pages
  • Google Scholar