Abstract
Fuzzy numbers are used to represent numerical quantities in a vague environment since the measurements are imprecise in nature in this environment. Ranking fuzzy numbers is then an important issue for decision-making problems in a fuzzy environment. Most of the existing ranking methods transform a fuzzy number into a real number based on certain criteria. On the other hand, other methods define a ranking index between two fuzzy sets or between a fuzzy set and others. However, there is yet no method that can always give a satisfactory solution. In this paper, the authors propose a new algorithm for ranking of trapezoidal fuzzy numbers. This method is based on the principle that there are only four possible topological configurations when we compare two trapezoidal fuzzy numbers. Moreover, the proposed method is consistent with our intuition and, when it is necessary, takes into account the decision-maker’s risk-attitude. The paper also presents several comparative examples and an application demonstrating the usage, advantages (simplicity, flexibility, practicability, etc.) and applicability of the proposed ranking method.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Marichal, J.-L.: Aggregation operators for multi criteria decision aid. Ph.D. Thesis, Department of Management, FEGSS. University of Liège (1998)
Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning, Part 1. Inf. Sci. 8(3), 199–249 (1975)
Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning, Part 2. Inf. Sci. 8(4), 301–357 (1975)
Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning, Part 3. Inf. Sci. 9(1), 43–80 (1975)
Merigó, J.M.: New extensions to the OWA operator and its application in business decision making. Ph.D. Thesis (In Spanish), Department of Business Administration, University of Barcelona (2008)
Merigó, J.M., Gil-Lafuente, A.: Fuzzy induced generalized aggregation operators and its application in multi person decision making. Expert Syst. Appl. 38(8), 9761–9772 (2011)
Simo, U.F., Gwét, H.: Fuzzy triangular aggregation operators. Int. J. Math. Math. Sci. (2018). https://doi.org/10.1155/2018/9209524
Jain, R.: Decision-making in the presence of fuzzy variables. IEEE Trans. Syst. Man Cybern. 6(10), 698–703 (1976)
Baldwin, J.F., Guild, N.C.F.: Comparison of fuzzy sets on the same decision space. Fuzzy Sets Syst. 2(3), 213–231 (1979)
Yager, R.R.: A procedure for ordering fuzzy subsets of the unit interval. Inf. Sci. 24(2), 143–161 (1981)
Dubois, D., Prade, H.: Ranking of fuzzy numbers in the setting of possibility theory. Inf. Sci. 30(3), 183–224 (1983)
Chen, S.H.: Ranking fuzzy numbers with maximizing set and minimizing set. Fuzzy Sets Syst. 17(2), 113–129 (1985)
Bortolan, G., Degani, R.: A review of some methods for ranking fuzzy subsets. Fuzzy Sets Syst. 15(1), 1–19 (1985)
Nakamura, K.: Preference relation on a set of fuzzy utilities as a basis for decision making. Fuzzy Sets Syst. 20(2), 147–162 (1986)
Lee, E.S., Li, R.L.: Comparison of fuzzy numbers based on the probability measure of fuzzy events. Comput. Math. Appl. 15(10), 887–896 (1988)
Kim, K., Park, K.: Ranking fuzzy numbers with index of optimism. Fuzzy Sets Syst. 35(2), 143–150 (1990)
Saade, J.J., Schwarzlander, H.: Ordering fuzzy sets over the real line: An approach based on decision making under uncertaintly. Fuzzy Sets Syst. 50(3), 237–246 (1992)
Liou, T.S., Wang, M.J.J.: Ranking fuzzy numbers with integral value. Fuzzy Sets Syst. 50(3), 247–255 (1992)
Choobineh, F., Li, H.: An index for ordering fuzzy numbers. Fuzzy Sets Syst. 54(4), 287–294 (1993)
Cheng, C.H.: A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets Syst. 95(3), 307–317 (1998)
Wang, X., Kerre, E.E.: Reasonable properties for the ordering of fuzzy quantities (I). Fuzzy Sets Syst. 118(3), 375–385 (2001)
Wang, X., Kerre, E.E.: Reasonable properties for the ordering of fuzzy quantities (II). Fuzzy Sets Syst. 118(3), 387–405 (2001)
Tran, L., Duckstein, L.: Comparison of fuzzy numbers using a fuzzy distance measure. Fuzzy Sets Syst. 130(3), 331–341 (2002)
Chu, T.C., Tsao, C.T.: Ranking fuzzy numbers with an area between the centroid point and original point. Comput. Math. Appl. 43(1), 111–117 (2002)
Abbasbandy, S., Asady, B.: Ranking of fuzzy numbers by sign distance. Inf. Sci. 176(16), 2405–2416 (2006)
Deng, Y., Zhenfu, Z., Qi, L.: Ranking fuzzy numbers with an area method using radius of gyration. Comput. Math. Appl. 51(6), 1127–1136 (2006)
Wang, Y.M., Yang, J.B., Xu, D.L., Chin, K.S.: On the centroids of fuzzy numbers. Fuzzy Sets Syst. 157(7), 919–926 (2006)
Asady, B., Zendehnam, A.: Ranking fuzzy numbers by distance minimization. Appl. Math. Model. 31(11), 2589–2598 (2007)
Wang, Z.X., Liu, Y.J., Fan, Z.P., Feng, B.: Ranking \(LR\)-fuzzy number based on deviation degree. Inf. Sci. 179(13), 2070–2077 (2009)
Abbasbandy, S., Hajjari, T.: A new approach for ranking of trapezoidal fuzzy numbers. Comput. Math. Appl. 57(3), 413–419 (2009)
Valvis, E.: A new linear ordering of fuzzy numbers on subsets of \(\widetilde{\cal{P}}(\mathbb{R})\). Fuzzy Optim. Decision Mak. 8(2), 141–163 (2009)
Wang, Y.M., Luo, Y.: Area ranking of fuzzy numbers based on positive and negative ideal points. Comput. Math. Appl. 58(9), 1769–1779 (2009)
Asady, B.: The revised method of ranking \(LR\) fuzzy number based on deviation degree. Expert Syst. Appl. 37(7), 5056–5060 (2010)
Asady, B.: Revision of distance minimization method for ranking of fuzzy numbers. Appl. Math. Model. 35(3), 1306–1313 (2011)
Ezzati, R., Allahviranloo, T., Khezerloo, S., Khezerloo, M.: An approach for ranking of fuzzy numbers. Expert Syst. Appl. 39(1), 690–695 (2012)
Boulmakoul, A., Laarabi, M.H., Sacile, R., Garbolino, E.: An original approach to ranking fuzzy numbers by inclusion index and bitset encoding. Fuzzy Optim. Decision Mak. 16(1), 23–49 (2017)
Yu, V.F., Van, L.H., Dat, L.Q., Chi, H.T.X., Chou, S.-Y., Duong, T.T.T.: Analyzing the ranking method for fuzzy numbers in fuzzy decision making based on the magnitude concepts. Int. J. Fuzzy Syst. 19(5), 1279–1289 (2017)
Firozja, M.A., Balf, F.R., Firouzian, S.: Vague ranking of fuzzy numbers. Math. Sci. 11(3), 189–193 (2017)
Dubois, D., Prade, H.: Fuzzy Sets and Systems: Theory and Applications. Academic Press, INC., London (1980)
Zimmermann, H.-J.: Fuzzy Sets Theory and Its Application. Kluwer Academic Press, Dordrecht (1991)
Acknowledgements
The authors are thankful to all the referees for their efficient comments and suggestions in obtaining the present form of the paper.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Simo, U.F., Gwét, H. A New Algorithm for Ranking of Trapezoidal Fuzzy Numbers. Int. J. Fuzzy Syst. 20, 2355–2367 (2018). https://doi.org/10.1007/s40815-018-0498-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40815-018-0498-z