164
Views
4
CrossRef citations to date
0
Altmetric
Original Articles

An approach to decision-making with triangular fuzzy reciprocal preference relations and its application

Pages 567-581 | Received 05 Feb 2017, Accepted 25 Nov 2017, Published online: 07 Dec 2017

References

  • Chang, D. Y. (1996). Application of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95, 649–655.
  • Dong, Y. C., & Herrera-Viedma, E. (2015). Consistency-driven automatic methodology to set interval numerical scales of 2-tuple linguistic term sets and its use in the linguistic GDM with preference relation. IEEE Transactions on Cybernetics, 45, 780–792.
  • Genç, S., Boran, F. E., Akay, D., & Xu, Z. S. (2010). Interval multiplicative transitivity for consistency, missing values and priority weights of interval fuzzy preference relations. Information Sciences, 180, 4877–4891.
  • Herrera-Viedma, E., Alonso, S., Chiclana, F., & Herrera, F. (2007). A consensus model for group decision making with incomplete fuzzy preference relations. IEEE Transactions on Fuzzy Systems, 15, 863–877.
  • Kwiesielewicz, M. (1998). A note on the fuzzy extension of Saaty's priority theory. Fuzzy Sets and Systems, 95, 161–172.
  • Leung, L. C., & Cao, D. (2000). On consistency and ranking of alternatives in fuzzy AHP. European Journal of Operational Research, 124, 102–113.
  • Liu, F., Zhang, W. G., & Zhang, L. H. (2014). Consistency analysis of triangular fuzzy reciprocal preference relations. European Journal of Operational Research, 235, 718–726.
  • Meng, F. Y., Chen, X. H., & Zhang, Y. L. (2016a). Consistency-based linear programming models for generating the priority vector from interval fuzzy preference relations. Applied Soft Computing, 41, 247–264.
  • Meng, F. Y., Lin, J., Tan, C. Q., & Zhang, Q. (2017a). A new multiplicative consistency based method for decision making with triangular fuzzy reciprocal preference relations.Fuzzy Sets and Systems., 315, 1–25. doi:10.1016/j.fss.2016.12.010.
  • Meng, F. Y., An, Q. X., Tan, C. Q., & Chen, X. H. (2017b). An approach for group decision making with interval fuzzy preference relations based on additive consistency and consensus analysis. IEEE Transactions on Systems, Man, and Cybernetics Systems., 47, 2069–2082. doi:10.1109/TSMC.2016.2606647.
  • Meng, F. Y., An, Q. X., & Chen, X. H. (2016b). A consistency and consensus-based method to group decision making with interval linguistic preference relations. Journal of the Operational Research Society, 67, 1419–1437.
  • Meng, F. Y., Tan, C. Q., & Chen, X. H. (2017c). Multiplicative consistency analysis for interval reciprocal preference relations: A comparative study. Omega, 68, 17–38.
  • Meng, F. Y., Chen, X. H., & Tan, C. Q. (2016c). Cooperative fuzzy games with interval characteristic functions. Operational Research. doi:10.1007/s12351-015-0183-z.
  • Meng, F. Y., & Chen, X. H. (2017). A new method for triangular fuzzy compare wise judgment matrix process based on consistency analysis. International Journal of Fuzzy Systems., 19, 27–46. doi:10.1007/s40815-016-0150-8.
  • Meng, F. Y., & Tan, C. Q. (2017). A new consistency concept for interval multiplicative preference relations. Applied Soft Computing., 52, 262–276. doi:10.1016/j.asoc.2016.11.001.
  • Mikhailov, L. (2003). Deriving priorities from fuzzy pairwise comparison judgments. Fuzzy Sets and Systems, 134, 365–385.
  • Mikhailov, L., & Tsvetinov, P. (2004). Evaluation of services using a fuzzy analytic hierarchy process. Applied Soft Computing, 5, 23–33.
  • Orlovsky, S. (1978). Decision-making with a fuzzy preference relation. Fuzzy Sets and Systems, 1, 155–167.
  • Pandey, A., & Kumar, A. (2016). A note on “Applying fuzzy linguistic preference relations to the improvement of consistency of fuzzy AHP.” Information Sciences, S, 346–347.
  • Podinovski, V. V. (2007). Interval articulation of superiority and precise elicitation of priorities. European Journal of Operational Research, 180, 406–417.
  • Ramk, J., & Korviny, P. (2010). Inconsistency of pair-wise comparison matrix with fuzzy elements based on geometric mean. Fuzzy Sets and Systems, 161, 1604–1613.
  • Rezaei, J., & Ortt, R. (2013). Multi-criteria supplier segmentation using a fuzzy preference relations based AHP. European Journal of Operational Research, 225, 75–84.
  • Rezaei, J., Ortt, R., & Scholten, V. (2013). An improved fuzzy preference programming to evaluate entrepreneurship Orientation. Applied Soft Computing, 13, 2749–2758.
  • Saaty, T. L. (1980). The analytic hierarchy process. New York, NY: McGraw-Hill.
  • Saaty, T. L., & Vargas, L. G. (1987). Uncertainty and rank order in the analytic hierarchy process. European Journal of Operational Research, 32, 107–117.
  • Sener, Z., & Karsak, E. E. (2011). A combined fuzzy linear regression and fuzzy multiple objective programming approach for setting target levels in quality function deployment. Expert Systems with Applications, 38, 3015–3022.
  • Tanino, T. (1984). Fuzzy preference orderings in group decision making. Fuzzy Sets and Systems, 12, 117–131.
  • Ureña, M. R., Chiclana, F., Morente-Molinera, J. A., & Herrera-Viedma, E. (2015). Managing incomplete preference relations in decision making: A review and future trends. Information Sciences, 302, 14–32.
  • van Laarhoven, P J. M. & Pedrycz, W. (1983). A fuzzy extension of Saaty's priority theory. Fuzzy Sets and Systems, 11, 229–241.
  • Wang, Y. M., Elhag, T. M. S., & Hua, Z. S. (2006). A modified fuzzy logarithmic least squares method for fuzzy analytic hierarchy process. Fuzzy Sets and Systems, 157, 3055–3071.
  • Wang, Y. M., & Chin, K. S. (2008). A linear goal programming priority method for fuzzy analytic hierarchy process and its applications in new product screening. International Journal of Approximate Reasoning, 49, 451–465.
  • Wang, Y. M., Yang, J. B., & Xu, D. L. (2005). A two-stage logarithmic goal programming method for generating weights from interval comparison matrices. Fuzzy Sets and Systems, 152, 475–498.
  • Wang, Y. M., & Elhag, T. M. S. (2007). A goal programming method for obtaining interval weights from an interval comparison matrix. European Journal of Operational Research, 177, 458–471.
  • Wang, T. C., & Chen, Y. H. (2008). Applying fuzzy linguistic preference relations to the improvement of consistency of fuzzy AHP. Information Sciences, 178, 3755–3765.
  • Wang, T. C., & Chen, Y. H. (2011). Fuzzy multi-criteria selection among transportation companies with fuzzy linguistic preference relations. Expert Systems with Applications, 38, 11884–11890.
  • Wang, Y. M., Luo, Y., & Hua, Z. (2008). On the extent analysis method for fuzzy AHP and its applications. European Journal of Operational Research, 186, 735–747.
  • Wang, Z. J. (2015). Consistency analysis and priority derivation of triangular fuzzy preference relations based on modal value and geometric mean. Information Sciences, 314, 169–183.
  • Wu, J., & Chiclana, F. (2014). Visual information feedback mechanism and attitudinal prioritisation method for group decision making with triangular fuzzy complementary preference relations. Information Sciences, 279, 716–734.
  • Xu, Z. S. (2011). Consistency of interval fuzzy preference relations in group decision making. Applied Soft Computing, 11, 3898–3909.
  • Xu, Z. S. (2001). A practical method for priority of interval number complementary judgment matrix. Operations Research and Management Science, 10, 16–19.
  • Xu, R. (2000). Fuzzy least-squares priority method in the analytic hierarchy process. Fuzzy Sets and Systems, 112, 359–404.
  • Xia, M. M., & Xu, Z. S. (2011). Methods for fuzzy complementary preference relations based on multiplicative consistency. Computers & Industrial Engineering, 61, 930–935.
  • Xu, Y. J., & Wang, H. M. (2014). A comment on “Incomplete fuzzy linguistic preference relations under uncertain environments.” Information Fusion, 20, 2–5.
  • Xu, Y., Li, K. W., & Wang, H. (2014). Incomplete interval fuzzy preference relations and their applications. Computers & Industrial Engineering, 67, 93–103.
  • Yager, R. R. (1980). A procedure for ordering fuzzy subsets of the unit interval. Information Sciences, 24, 143–161.
  • Yuen, K. K. F., & Lau, H. C. W. (2011). A fuzzy group analytical hierarchy process approach for software quality assurance management: Fuzzy logarithmic least squares method. Expert Systems with Applications, 38, 10292–10302.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.