You are here

Ranking Generalized Trapezoidal Fuzzy Numbers with Euclidean Distance by the Incentre of Centroids

Journal Name:

Publication Year:

Author Name
Abstract (2. Language): 
This paper proposes a method on the incentre of Centroids and uses of Euclidean distance to ranking generalized fuzzy numbers. In this method, splitting the generalized trapezoidal fuzzy numbers into three plane figures and then calculating the centroids of each plane figure followed by the incentre of the centroids and then finding the Euclidean distance. For the validation the results of the proposed approach are compared with different existing approaches.
103-114

REFERENCES

References: 

[1] Abbasbandy, S., Hajjari, T ., A new approach for ranking of trapezoidal
fuzzy numbers. Computers and Mathematics with Applications, 57 (3),
(2009) 413-419.
[2] Chen, S. J., Chen, S. M, A new method for handling multicriteria fuzzy
decision making problems using FN-IOWA operators. Cybernatics and
Systems, 34, (2003) 109-137.
112 Salim Rezvani
[3] Chen, SJ., Chen, SM., Fuzzy risk analysis based on the ranking of generalized
trapezoidal fuzzy numbers. Applied Intelligence, 26 (1), (2007)
1-11.
[4] Chen, SM., Chen, JH., Fuzzy risk analysis based on ranking generalized
fuzzy numbers with different heights and different spreads. Expert Systems
with Applications, 36 (3), (2009) 6833-6842.
[5] Cheng, C. H.,A new approach for ranking fuzzy numbers by distance
method. Fuzzy Sets and System, 95, (1998) 307-317.
[6] 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, (2002) 111-117.
[7] Fateen Najwa Azman and Lazim Abdullah, Review on Ranking Fuzzy
Numbers Using The Centroid Point Method (2011).
[8] Kumar, A., Singh P., Kaur A., Kaur, P., RM approach for ranking of generalized
trapezoidal fuzzy numbers. Fuzzy Information and Engineering,
2 (1),(2010) 37-47.
[9] Murakami, S., Maeda, S., Imamura, S., Fuzzy decision analysis on the
development of centralized regional energy control; system. Paper presented
at the IFAC Symp on Fuzzy Inform. Knowledge Representation
and Decision Analysis (1983).
[10] Pushpinder Singh et al, Ranking of Generalized Trapezoidal Fuzzy Numbers
Based on Rank, Mode, Divergence and Spread, Turkish Journal of
Fuzzy Systems, Vol.1, No.2, (2010) pp. 141-152.
[11] S. Rezvani, Three-tier FMCDM Problems with Trapezoidal Fuzzy Number,
World Applied Sciences Journal 10 (9):(2010) 1106-1113.
[12] S. Rezvani, Multiplication Operation on Trapezoidal Fuzzy Numbers,
Journal of Physical Sciences, Vol. 15, (2011) 17-26.
[13] S. Rezvani, A New Method for Ranking in Perimeters of two Generalized
Trapezoidal Fuzzy Numbers,International Journal of Applied Operational
Research, Vol. 2, No. 3, (2012) pp. 83-90.
[14] S. Rezvani, A New Approach Ranking of Exponential Trapezoidal Fuzzy
Numbers,Journal of Physical Sciences, Vol. 16, (2012) 45-57.
[15] S. Rezvani, A New Method for Ranking in Areas of two Generalized
Trapezoidal Fuzzy Numbers, International Journal of Fuzzy Logic Systems
(IJFLS) Vol.3, No1, (2013) 17-24.
Ranking Generalized Trapezoidal Fuzzy Numbers with Euclidean... 113
[16] S. Rezvani, Ranking Method of Trapezoidal Intuitionistic Fuzzy Numbers,
Annals of Fuzzy Mathematics and Informatics, 2013, IN PRESS.
[17] Y. L. P. Thorani et al, Ordering Generalized Trapezoidal Fuzzy Numbers,
Int. J. Contemp. Math. Sciences, Vol. 7, no. 12, (2012) 555 - 573.
[18] Wang, Y. M., Yang, J. B., Xu, D. L., Chin, K. S, On the centroid of fuzzy
numbers. Fuzzy Sets and Systems, 157, (2006) 919-926.
[19] Wang, Y. J., Lee, H. S, The revised method of ranking fuzzy numbers
with an area between the centroid and original points. Computers and
Mathematics with Applications, 55, (2008) 2033-2042.
[20] Yager, R. R,On a general class of fuzzy connectives. Fuzzy Sets and Systems,
4(6), (1980) 235-242.

Thank you for copying data from http://www.arastirmax.com