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Issue:Hesitant intuitionistic fuzzy linguistic term sets

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Title of paper: Hesitant intuitionistic fuzzy linguistic term sets
Ismat Beg
Lahore School of Economics, Lahore, Pakistan
Tabasam Rashid
University of Management and Technology, Lahore, Pakistan
Published in: "Notes on IFS", Volume 20, 2014, Number 3, pages 53-64
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Abstract: Dealing with uncertainty is a challenging problem, and different tools have been proposed in the literature to deal with it. Intuitionistic fuzzy sets was presented to manage situations in which experts have some membership and non-membership value to assess an alternative. Hesitant fuzzy linguistic term sets was used to handle such situations in which experts hesitate between several possible linguistic values or interval to assess an alternative and variable in qualitative settings. In this paper, the concept of an hesitant intuitionistic fuzzy linguistic term set is introduced to provide a linguistic and computational basis to manage the situations in which experts assess an alternative in possible linguistic interval and impossible linguistic interval. Distance measure is defined between any two elements of hesitant intuitionistic fuzzy linguistic term set. Technique for order preference by similarity to ideal solution is proposed in hesitant intuitionistic fuzzy linguistic term set setting for multi-criteria group decision making. An example is given to elaborate the proposed method for the selection of the best alternative as well as rank the alternatives from the best to worst.
Keywords: Hesitant fuzzy set, Intuitionistic fuzzy set, Linguistic decision making, TOPSIS.
AMS Classification: 91B10, 91B06, 90B50, 62C86.
  1. Atanassov, K. Intuitionistic fuzzy sets, Fuzzy Sets and Systems, Vol. 20, 1986, 87–96.
  2. Atanassov, K. Intuitionistic Fuzzy Sets, Heidelberg: Springer, 1999.
  3. Beg, I., T. Rashid, TOPSIS for Hesitant Fuzzy Linguistic Term Sets, International Journal of Intelligent Systems, Vol. 28, 2013, 1162–1171.
  4. Beg, I., T. Rashid, Multi-criteria trapezoidal valued intuitionistic fuzzy decision making with Choquet integral based TOPSIS, OPSEARCH, Vol. 51, 2014, No. 1, 98–129.
  5. Boran, F. E., S. Gen, M. Kurt and D. Akay, A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method, Expert Systems with Applications, Vol. 36, 2009, 11363–11368.
  6. Chen, C. T. Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems, Vol. 114, 2000, 1–9.
  7. Chen, S. J., C. L. Hwang, Fuzzy Multiple Attribute Decision Making, Berlin: Springer, 1992.
  8. Chu, T.-C., Y.-C. Lin, An interval arithmetic based fuzzy TOPSIS model, Expert Systems with Applications, Vol. 36, 2009, 10870–10876.
  9. De, S. K., R. Biswas, A. R. Roy, An application of intuitionistic fuzzy sets in medical diagnosis, Fuzzy Sets and Systems, Vol. 117, 2001, 209–213.
  10. Hwang, C. L., K. Yoon, Multiple attributes decision making methods and applications, Berlin, Heidelberg: Springer, 1981.
  11. Li, D.-F. Multiattribute decision making models and methods using intuitionistic fuzzy sets, Journal of Computer and System Sciences, Vol. 70, 2005, 73–85.
  12. Liu, H., R. M. Rodr´ıguez, A fuzzy envelope for hesitant fuzzy linguistic term set and its application to multicriteria decision making, Information Sciences, Vol. 258, 2014, 220–238.
  13. Martınez, L., D. Ruan, F. Herrera, Computing with words in decision support systems: an overview on models and applications, International Journal Computational Intelligence Systems, Vol. 3, 2010, No. 4, 382–395.
  14. Mendel, J. M. An architecture for making judgement using computing with words, International Journal of Applied Mathematics and Computer Science, Vol. 12, 2002, No. 3, 325–335.
  15. Rashid, T., I. Beg, S. M. Husnine, Robot selection by using generalized interval-valued fuzzy numbers with TOPSIS, Applied Soft Computing, Vol. 21, 2014, 462–468.
  16. Rodr´ıguez, R. M., L. Mart´ınez, An Analysis of Symbolic Linguistic Computing Models in Decision Making, International Journal of General Systems, Vol. 42, 2013, No. 1, 121–136.
  17. Rodr´ıguez, R. M., L. Mart´ınez and F. Herrera, Hesitant fuzzy linguistic term sets for decision making, IEEE Transactions of Fuzzy Systems, Vol. 20, 2012, No. 1, 109–119.
  18. Rodr´ıguez, R. M., L. Mart´ınez and F. Herrera, A group decision making model dealing with comparative linguistic expressions based on hesitant fuzzy linguistic term sets, Information Sciences, Vol. 241, 2013, No. 1, 28–42.
  19. Torra, V. Hesitant fuzzy sets, International Journal of Intelligent Systems, Vol. 25, 2010, No. 6, 529–539.
  20. Wang, T. C., T. H. Chang, Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment, Expert Systems with Applications, Vol. 33, 2007, 870–880.
  21. Xu, Z. S., J. Chen, An interactive method for fuzzy multiple attribute group decision making, Information Sciences, Vol. 177, 2007, No. 1, 248–263.
  22. Zadeh, L. A. Fuzzy sets, Information and Control, Vol. 8, 1965, 338–356.
  23. Zadeh, L. A. The concept of a linguistic variable and its applications to approximate reasoning, Information Sciences, Part I, II, III Vol. 8, 9, 1975, pages 199–249, 301–357, 43–80.

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