A New Approach for Choosing the Most Appropriate Fuzzy Ranking Algorithm for Solving MADM Problems

  • Fahimeh RamezaniEmail author
  • Jie Lu
Part of the Studies in Computational Intelligence book series (SCI, volume 391)


There are many fuzzy ranking algorithms available to solve multi-attribute decision making (MADM) problems. Some are more suitable than others for particular decision problems. This paper proposes a new method for choosing the most appropriate fuzzy ranking algorithm for solving MADM problems based on the type and number of attributes and the number of alternatives, considering the least time consumption and the least computation for ranking alternatives. In addition, we develop a software to simulate three main fuzzy ranking algorithms: SAW, Negi, and Chen and Hwang (Chen and Hwang 1992). This software can be used in any MADM decision support system.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Baas, S.M., Kwakernak, H.: Rating and ranking of multiple aspect alternatives using fuzzy sets. Automatica 13, 47–58 (1977)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Belton, V.: A comparison of the analytic hierarchy process and a simple multi-attribute value function. European Journal of Operational Research 26, 7–21 (1986)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Bonissone, P.P.: A fuzzy sets based linguistic approach: theory and applications. In: Gupta, M.M., Sanchez, E. (eds.) Approximate reasoning in decision analysis. North Holland, Amsterdam (1982)Google Scholar
  4. 4.
    Chen, S.H.: Ranking fuzzy numbers with maximizing set and minimizing set. Fuzzy set and systems 17(2), 113–129 (1985)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Chen, S.J., Hwang, C.L.: Fuzzy multiple attribute decision making. Springer, Berlin (1992)CrossRefGoogle Scholar
  6. 6.
    Chen, S.M.: A new approach to handling fuzzy decision-making problems. In: Proceedings of the 18th International Symposium of Multiple Valued logic, Spain, pp. 72–76 (1988)Google Scholar
  7. 7.
    Colson, G., Bruyn, C.: Models and methods in multiple criteria decision making. Pergamon, Oxford (1989)Google Scholar
  8. 8.
    Dyer, J.S., Fishburn, P.C., Steuer, R.E., Wallenius, J., Zionts, S.: Multiple criteria decision making, multi attribute utility theory: the next ten years. Management Science 38, 645–653 (1992)CrossRefGoogle Scholar
  9. 9.
    Efstathiou, J., Rajkovic, V.: Multi attribute decision making using a fuzzy heuristic approach. IEEE Transactions on System Man and Cybernetics 9, 326–333 (1979)CrossRefGoogle Scholar
  10. 10.
    Efstathiou, J., Tong, R.: Ranking fuzzy sets: a decision theoretic approach. IEEE Transactions on System Man and Cybernetics 12, 655–659 (1982)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Fishburn, P.C.: Additive utilities with incomplete product set: applications to priorities and assignments. ORSA Publication, Baltimore (1967)Google Scholar
  12. 12.
    Hwang, C.L., Yoon, K.: Multiple attribute decision making. Springer, Heidelberg (1981)CrossRefGoogle Scholar
  13. 13.
    Jain, R.: Decision making in the presence of fuzzy variables. IEEE Transactions on Systems Man and Cybernetics 6, 698–703 (1976)zbMATHGoogle Scholar
  14. 14.
    Jain, R.: A procedure for multi aspect decision making using fuzzy sets. International Journal of System Science 8, 1–7 (1977)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Karni, R., Sanchez, P., Tummala, V.M.R.: A comparative study of multi-attribute decision making methodologies. Theory and Decision 29, 203–222 (1990)CrossRefGoogle Scholar
  16. 16.
    Kerre, E.E.: The use of fuzzy set theory in electro cardio logical diagnostics. In: Gupta, M.M., Sanchez, E. (eds.) Approximate Reasoning in Decision Analysis. North-Holland, Amsterdam (1982)Google Scholar
  17. 17.
    Lee, E.S., Li, R.L.: Comparison of fuzzy numbers based on the probability measure of fuzzy events. Computers and Mathematics with Applications 15, 887–896 (1988)MathSciNetCrossRefGoogle Scholar
  18. 18.
    MacCrimmon, K.R.: Decision making among multiple attribute alternatives: a survey and consolidated approach. Rand memorandum RM-4823-ARPA, Washington, DC (1968)Google Scholar
  19. 19.
    Olson, D.L., Moshkovich, H.M., Schellenberger, R., Mechitov, A.I.: Consistency and accuracy in decision aids: Experiments with four multiattribute systems. Decision Sciences 26, 723–748 (1995)CrossRefGoogle Scholar
  20. 20.
    Stewart, T.J.: A critical study on the status of multiple criteria decision making: theory and practice. Omega 20, 569–586 (1992)CrossRefGoogle Scholar
  21. 21.
    Wenstop, F.: Fuzzy set simulation models in a systems dynamic perspective. Kybernetes 6, 209–218 (1976)CrossRefGoogle Scholar
  22. 22.
    Yeh, C.H.: A problem-based selection of multi-attribute decision-making methods. International Transactions in Operational Research 9, 169–181 (2002)CrossRefGoogle Scholar
  23. 23.
    Zanakis, S.H., Solomon, A., Wishart, N., Dublish, S.: Multi-attribute decision making: a simulation comparison of select methods. European Journal of Operational Research 107, 507–529 (1998)CrossRefGoogle Scholar
  24. 24.
    Zeleny, M.: Multiple criteria decision making. McGraw-Hill, New York (1982)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.School of Software, Faculty of Engineering and Information TechnologyUniversity of TechnologySydneyAustralia

Personalised recommendations