Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Journal of Artificial Intelligence and Soft Computing Research

The Journal of Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology

4 Issues per year

Open Access
Online
ISSN
2083-2567
See all formats and pricing
More options …

Modelling Uncertainties in Multi-Criteria Decision Making using Distance Measure and TOPSIS for Hesitant Fuzzy Sets

Ismat Beg / Tabasam Rashid
Published Online: 2017-02-23 | DOI: https://doi.org/10.1515/jaiscr-2017-0007

Abstract

A notion for distance between hesitant fuzzy data is given. Using this new distance notion, we propose the technique for order preference by similarity to ideal solution for hesitant fuzzy sets and a new approach in modelling uncertainties. An illustrative example is constructed to show the feasibility and practicality of the new method.

Keywords: uncertainty modelling; multiple criteria analysis; group decisions and negotiations; hesitant fuzzy set; TOPSIS

MSC 2010: 91B06; 91B10; 03B52; 03E72; 68T37

References

  • [1] B. Ashtiani, F. Haghighirad, A. Makui and G. Montazer, Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets, Applied Soft Computing, 9(2), 2009, 457–461CrossrefWeb of ScienceGoogle Scholar

  • [2] I. Beg and T. Rashid, Multi-criteria trapezoidal valued intuitionistic fuzzy decision making with Choquet integral based TOPSIS, OPSEARCH, 51(1), 2014, 98-129CrossrefGoogle Scholar

  • [3] I. Beg and T. Rashid, TOPSIS for hesitant fuzzy linguistic term sets, International Journal of Intelligent Systems, 28, 2013, 1162–1171Google Scholar

  • [4] R. E. Bellman and L. A. Zadeh, Decision making in a fuzzy environment, Management Science, 17(4), 1970, 141-164CrossrefGoogle Scholar

  • [5] F. E. Boran, 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, 36, 2009, 11363–11368Google Scholar

  • [6] C. T. Chen, Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems, 114, 2000) 1–9Google Scholar

  • [7] S. J. Chen and C. L. Hwang, Fuzzy multiple attribute decision making, Berlin: Springer, 1992)Google Scholar

  • [8] T.-C. Chu and Y.-C. Lin, An interval arithmetic based fuzzy TOPSIS model, Expert Systems with Applications, 36, 2009, 10870–10876Google Scholar

  • [9] D. Dubois, The role of fuzzy sets in decision sciences: Old techniques and new directions, Fuzzy Sets and Systems, 184, 2011, 3–28Google Scholar

  • [10] F. Herrera, E. Herrera-Viedma and L. Martinez, A fusion approach for managing multi-granularity linguistic term sets in decision making, Fuzzy Sets and Systems, 114, 2000, 43–58Google Scholar

  • [11] C. L. Hwang and K. Yoon, Multiple attributes decision making methods and applications, Berlin, Heidelberg: Springer, 1981)Google Scholar

  • [12] G. R. Jahanshahloo, H. F. Lotfi and M. Izadikhah, Extension of the TOPSIS method for decision-making problems with fuzzy data, Applied Mathematics and Computation, 181(2), 2006, 1544–1551Google Scholar

  • [13] J. Jiang, Y.-W. Chen, Y.-W. Chen, K.-W. Yang, TOPSIS with fuzzy belief structure for group belief multiple criteria decision making, Expert Systems with Applications, 38, 2011, 9400–9406Google Scholar

  • [14] T. Kaya and C. Kahraman, Multicriteria decision making in energy planning using a modified fuzzy TOPSIS methodology, Expert Systems with Applications, 38(6), 2011, 6577–6585CrossrefGoogle Scholar

  • [15] G. Kim, C. Park and K. Yoon, Identifying investment opportunities for advanced manufacturing systems with comparative-integrated, International Journal of Production Economics, 50, 1997, 23-33Google Scholar

  • [16] M. S. Kuo, G. H. Tzeng and W. C. Huang, Group decision-making based on concepts of ideal and anti-ideal points in a fuzzy environment, Mathematical and Computer Modelling, 45, 2007, 324–339Google Scholar

  • [17] I. Mahdavi, N. Mahdavi-Amiri, A. Heidarzade and R. Nourifar, Designing a model of fuzzy TOPSIS in multiple criteria decision making, Applied Mathematics and Computation, 206, 2008, 607–617Google Scholar

  • [18] D. S. Negi, Fuzzy analysis and optimization, PhD thesis. Department of Industrial Engineering, Kansas State University, 1989)Google Scholar

  • [19] J. Peng, J. Wang, J. Wang, L. Yang and X. Chen, An extension of ELECTRE to multi-criteria decision-making problems with multi-hesitant fuzzy sets. Information Sciences, 307, 2015, 113–126Web of ScienceGoogle Scholar

  • [20] T. Rashid, I. Beg and S. M. Husnine, Robot selection by using generalized interval-valued fuzzy numbers with TOPSIS, Applied Soft Computing. Applied Soft Computing, 21, 2014, 462–468CrossrefWeb of ScienceGoogle Scholar

  • [21] R. M. Rodriguez, L. Martinez and F. Herrera, Hesitant fuzzy linguistic term sets for decision making, IEEE Transaction on fuzzy Systems 20(1), 2012, 109–118Google Scholar

  • [22] H. Shih, H. Shyur and E. Lee, An extension of TOPSIS for group decision making, Mathematical and Computer Modelling, 45, 2007, 801–813Google Scholar

  • [23] V. Torra, Hesitant fuzzy sets, International Journal of Intelligent Systems, 25(6), 2010, 529–539Google Scholar

  • [24] T. C. Wang and T. H. Chang, Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment, Expert Systems with Applications, 33, 2007, 870–880Google Scholar

  • [25] J. H. Wang and J. Y. Hao, A new version of 2-tuple fuzzy linguistic representation model for computing with words, IEEE Transactions on Fuzzy Systems, 14(3), 2006, 435–445Google Scholar

  • [26] Y. J. Wang and H. S. Lee, Generalizing TOPSIS for fuzzy multiple-criteria group decision-making, Computers and Mathematics with Applications, 53, 2007, 1762–1772Google Scholar

  • [27] G. Wei, Hesitant fuzzy prioritized operators and their application to multiple attribute decision making, Knowledge-Based Systems 31, 2012, 176-182Google Scholar

  • [28] M. Xia and Z. Xu, Hesitant fuzzy information aggregation in decision making, International Journal of Approximate Reasoning, 52, 2011, 395–407Google Scholar

  • [29] Z. Xu and M. Xia, On distance and correlation measures of hesitant fuzzy information, International Journal of Intelligent Systems, 26, 2011, 410–425Google Scholar

About the article

Published Online: 2017-02-23

Published in Print: 2017-04-01


Citation Information: Journal of Artificial Intelligence and Soft Computing Research, Volume 7, Issue 2, Pages 103–109, ISSN (Online) 2083-2567, DOI: https://doi.org/10.1515/jaiscr-2017-0007.

Export Citation

© 2017 Academy of Management (SWSPiZ), Lodz. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

Comments (0)

Please log in or register to comment.
Log in