×

Ranking \(L-R\) fuzzy number based on deviation degree. (English) Zbl 1166.90349

Summary: This paper proposed a novel approach to ranking fuzzy numbers based on the left and right deviation degree (\(L-R\) deviation degree). In the approach, the maximal and minimal reference sets are defined to measure \(L-R\) deviation degree of fuzzy number, and then the transfer coefficient is defined to measure the relative variation of \(L-R\) deviation degree of fuzzy number. Furthermore, the ranking index value is obtained based on the \(L-R\) deviation degree and relative variation of fuzzy numbers. Additionally, to compare the proposed approach with the existing approaches, five numerical examples are used. The comparative results illustrate that the approach proposed in this paper is simpler and better.

MSC:

90B50 Management decision making, including multiple objectives
90C70 Fuzzy and other nonstochastic uncertainty mathematical programming
Full Text: DOI

References:

[1] Abbasbandy, S.; Asady, B., Ranking of fuzzy numbers by sign distance, Information Sciences, 176, 2405-2416 (2006) · Zbl 1293.62008
[2] Asady, B.; Zendehnam, A., Ranking fuzzy numbers by distance minimization, Applied Mathematical Modelling, 31, 2589-2598 (2007) · Zbl 1211.03069
[3] Bortolan, G.; Degani, R., A review of some methods for ranking fuzzy subsets, Fuzzy Sets and Systems, 15, 1-19 (1985) · Zbl 0567.90056
[4] Cheng, C. H., A new approach for ranking numbers by distance method, Fuzzy Sets and Systems, 95, 307-317 (1998) · Zbl 0929.91009
[5] Chen, S. J.; Hwang, C. L., Fuzzy Multiple Attribute Decision Making (1992), Springer: Springer Berlin · Zbl 0768.90042
[6] Chen, L. H.; Lu, H. W., An approximate approach for ranking fuzzy numbers based on left and right dominance, Computers and Mathematics with Applications, 41, 1589-1602 (2001) · Zbl 0984.03041
[7] Chen, L. H.; Lu, H. W., The preference order of fuzzy numbers, Computers and Mathematics with Applications, 44, 1455-1465 (2002) · Zbl 1104.91300
[8] Cheng, C. H.; Mon, D. L., Fuzzy system reliability analysis by confidence interval, Fuzzy Sets and Systems, 56, 29-35 (1993)
[9] Chu, T. C.; Tsao, C. T., Ranking fuzzy numbers with an area between the centroid point and original point, Computers and Mathematics with Applications, 43, 1/2, 111-117 (2002) · Zbl 1113.62307
[10] Deng, Y.; Zhu, Z. F.; Liu, Q., Ranking fuzzy numbers with an area method using Radius of Gyration, Computers and Mathematics with Applications, 51, 1127-1136 (2006) · Zbl 1134.68526
[11] Fortemps, P.; Roubens, M., Ranking and defuzzification methods based on area compensation, Fuzzy Sets and Systems, 82, 319-330 (1996) · Zbl 0886.94025
[12] Jain, R., A procedure for multi-aspect decision making using fuzzy sets, International Journal of Systems Science, 8, 1-7 (1978) · Zbl 0347.90001
[13] Kaufman, A.; Gupta, M. M., Introduction to fuzzy arithmetic: theory and application: (1991), Van Nostrand Reinhold: Van Nostrand Reinhold New York · Zbl 0754.26012
[14] Kwang, H. L.; Lee, J. H., A method for ranking fuzzy numbers and its application to decision-making, IEEE Transactions on Fuzzy Systems, 7, 677-685 (1999)
[15] Lee, E. S.; Li, R. J., Comparison of fuzzy numbers based on the probability measure of fuzzy events, Computers and Mathematics with Applications, 15, 887-896 (1988) · Zbl 0654.60008
[16] Lious, T. S.; Wang, M. J., Ranking fuzzy numbers with integral value, Fuzzy Sets and Systems, 5, 247-255 (1992) · Zbl 1229.03043
[17] Liu, X. W.; Han, S. L., Ranking fuzzy numbers with preference weighting function expectations, Computers and Mathematics with Applications, 49, 1731-1753 (2005) · Zbl 1078.91005
[18] Liu, X., Measuring the satisfaction of constraints in fuzzy linear programming, Fuzzy Sets and Systems, 122, 263-275 (2001) · Zbl 1015.90098
[19] Matarazzo, B.; Munda, G., New approaches for the comparison of \(L-R\) fuzzy numbers: a theoretical and operational analysis, Fuzzy Sets and Systems, 118, 407-418 (2001) · Zbl 0972.03055
[20] Mitchell, H. B.; Schaefer, P. A., On ordering fuzzy numbers, International Journal of Intelligent Systems, 15, 981-993 (2000) · Zbl 0960.68046
[21] Tran, L.; Duckein, L., Comparison of fuzzy numbers using a fuzzy distance measure, Fuzzy Sets and Systems, 35, 331-341 (2002) · Zbl 1023.03543
[22] Wang, X.; Kerre, E. E., Reasonable properties for the ordering of fuzzy quantities, Fuzzy Sets and Systems, 118, 375-385 (2001) · Zbl 0971.03054
[23] Wang, Y. J.; Lee, S. H., The revised method of ranking fuzzy numbers with an area between the centroid and original points, Computers and Mathematics with Applications, 55, 2033-2042 (2008) · Zbl 1137.62313
[24] Wang, Y. M.; Yang, J. B.; Xu, D. L.; Chin, KS., On the centroids of fuzzy numbers, Fuzzy Sets and Systems, 157, 919-926 (2006) · Zbl 1099.91035
[25] Wang, M. L.; Wang, H. F.; Lung, L. C., Ranking fuzzy number based on lexicographic screening procedure, International Journal of Information Technology and Decision Making, 4, 663-678 (2005)
[26] Yager, R. R., In a general class of fuzzy connectives, Fuzzy Sets and Systems, 4, 235-242 (1980) · Zbl 0443.04008
[27] Yager, R. R.; Dimitar, F., On ranking fuzzy numbers using valuations, International Journal of Intelligent Systems, 14, 1249-1268 (1999) · Zbl 0937.68115
[28] Yager, R. R.; Detyniecki, M.; Meunier, B. B., A context-dependent method for ordering fuzzy numbers using probabilities, Information Sciences, 138, 237-255 (2001) · Zbl 0996.03511
[29] Yao, J. S.; Lin, F. T., Fuzzy critical path method based on signed distance ranking of fuzzy numbers, IEEE Transactions on Systems Man, and Cybernetics, Part A: Systems and Humans, 30, 76-82 (2000)
[30] Yao, J. S.; Wu, K., Ranking fuzzy numbers based on decomposition principle and signed distance, Fuzzy Sets and Systems, 116, 275-288 (2000) · Zbl 1179.62031
[31] Yoon, K. P., A probabilistic approach to rank complex fuzzy numbers, Fuzzy Sets and Systems, 80, 167-176 (1996)
[32] Zadeh, L. A., Fuzzy sets, Information and Control, 8, 338-353 (1965) · Zbl 0139.24606
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.