Fuzzy weighted average as a fuzzified aggregation operator and its properties
Kybernetika, Tome 53 (2017) no. 1, pp. 137-160
Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

Voir la notice de l'article

The weighted average is a well-known aggregation operator that is widely applied in various mathematical models. It possesses some important properties defined for aggregation operators, like monotonicity, continuity, idempotency, etc., that play an important role in practical applications. In the paper, we reveal whether and in which way such properties can be observed also for the fuzzy weighted average operator where the weights as well as the weighted values are expressed by noninteractive fuzzy numbers. The usefulness of the obtained results is discussed and illustrated by several numerical examples.
The weighted average is a well-known aggregation operator that is widely applied in various mathematical models. It possesses some important properties defined for aggregation operators, like monotonicity, continuity, idempotency, etc., that play an important role in practical applications. In the paper, we reveal whether and in which way such properties can be observed also for the fuzzy weighted average operator where the weights as well as the weighted values are expressed by noninteractive fuzzy numbers. The usefulness of the obtained results is discussed and illustrated by several numerical examples.
DOI : 10.14736/kyb-2017-1-0137
Classification : 03E72, 68T37
Keywords: aggregation operator; fuzzy weighted average; fuzzy numbers; fuzzy weights
@article{10_14736_kyb_2017_1_0137,
     author = {Pavla\v{c}ka, Ond\v{r}ej and Pavla\v{c}kov\'a, Martina and Hetflei\v{s}, Vladislav},
     title = {Fuzzy weighted average as a fuzzified aggregation operator and its properties},
     journal = {Kybernetika},
     pages = {137--160},
     year = {2017},
     volume = {53},
     number = {1},
     doi = {10.14736/kyb-2017-1-0137},
     mrnumber = {3638561},
     zbl = {06738599},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.14736/kyb-2017-1-0137/}
}
TY  - JOUR
AU  - Pavlačka, Ondřej
AU  - Pavlačková, Martina
AU  - Hetfleiš, Vladislav
TI  - Fuzzy weighted average as a fuzzified aggregation operator and its properties
JO  - Kybernetika
PY  - 2017
SP  - 137
EP  - 160
VL  - 53
IS  - 1
UR  - http://geodesic.mathdoc.fr/articles/10.14736/kyb-2017-1-0137/
DO  - 10.14736/kyb-2017-1-0137
LA  - en
ID  - 10_14736_kyb_2017_1_0137
ER  - 
%0 Journal Article
%A Pavlačka, Ondřej
%A Pavlačková, Martina
%A Hetfleiš, Vladislav
%T Fuzzy weighted average as a fuzzified aggregation operator and its properties
%J Kybernetika
%D 2017
%P 137-160
%V 53
%N 1
%U http://geodesic.mathdoc.fr/articles/10.14736/kyb-2017-1-0137/
%R 10.14736/kyb-2017-1-0137
%G en
%F 10_14736_kyb_2017_1_0137
Pavlačka, Ondřej; Pavlačková, Martina; Hetfleiš, Vladislav. Fuzzy weighted average as a fuzzified aggregation operator and its properties. Kybernetika, Tome 53 (2017) no. 1, pp. 137-160. doi: 10.14736/kyb-2017-1-0137

[1] Baas, S., Kwakernaak, H.: Rating and ranking of multiple-aspect alternatives using fuzzy sets. Automatica 13 (1977), 47-58. | DOI | MR

[2] Beliakov, G., Pradera, A., Calvo, T.: Aggregation Functions: A Guide for Practitioners. Springer-Verlag, Berlin 2007.

[3] Calvo, T., Mayor, G., (eds.), R. Mesiar: Aggregation Operators: New Trends and Applications. Physica-Verlag, Heidelberg 2002. | DOI | MR | Zbl

[4] Campos, L. M. De, Heute, J. F., Moral, S.: Probability intervals: a tool for uncertain reasoning. Int. J. Uncertainty, Fuzziness and Knowledge-Based Systems 2 (1994), 167-196. | DOI | MR

[5] Dong, W. M., Wong, F. S.: Fuzzy weighted averages and implementation of the extension principle. Fuzzy Sets and Systems 21 (1987), 183-199. | DOI | MR | Zbl

[6] Dubois, D.: Fuzzy weighted averages and fuzzy convex sums: Authors response. Fuzzy Sets and Systems 213 (2013), 106-108. | DOI | MR

[7] Dubois, D., Prade, H.: Additions of interactive fuzzy numbers. IEEE Trans. Automat. Control 26(1981), 4, 926-936. | DOI | MR

[8] Fodor, J. C., Roubens, M.: Fuzzy Preference Modelling and Multicriteria Decision Support. Kluwer Academic Publishers, Dordrecht 1994. | DOI | Zbl

[9] Ghazinoory, S., Zadeh, A. E., Kheirkhah, A. S.: Application of fuzzy calculations for improving portfolio matrices. Inform. Sci. 180 (2010), 9, 1582-1590. | DOI

[10] Grabisch, M., Marichal, J. L., Mesiar, R., Pap, E.: Aggregation Functions. Cambridge University Press, Cambridge 2009. | DOI | MR | Zbl

[11] Guh, Y.-Y., Hong, C. C., Wang, K. M., Lee, E. S.: Fuzzy weighted average: A max-min paired elimination method. Comp. Math. Appl. 32 (1996), 115-123. | DOI

[12] Guh, Y. Y., Hon, C. C., Lee, E. S.: Fuzzy weighted average: The linear programming approach via Charness and Coopers rule. Fuzzy Sets and Systems 117 (2001), 1, 157-160. | DOI | MR

[13] Hung, K. C., Julian, P., Chien, T., Jin, W. T. H.: A decision support system for engineering design based on an enhanced fuzzy MCDM approach. Expert Systems Appl. 37 (1) (2010), 202-213. | DOI

[14] Chang, P. T., Hung, K. C.: Applying thefFuzzy-weighted-average approach to evaluate network security systems. Comp. Math. Appl. 49 (2005), 1797-1814. | DOI | MR

[15] Kao, C., Liu, S. T.: Fractional programming approach to fuzzy weighted average. Fuzzy Sets and Systems 120 (2001), 3, 435-444. | DOI | MR | Zbl

[16] Kaufmann, A., Gupta, M. M.: Introduction to Fuzzy Arithmetic: Theory and Applications. (Second edition). Van Nostrand Reinhold, New York 1991. | MR

[17] Klir, G. J., Pan, Y.: Constrained fuzzy arithmetic: Basic questions and some answers. Soft Computing 2 (1998), 100-108. | DOI

[18] Klir, G. J., Yuan, B.: Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice Hall, New Jersey, 1996. | MR | Zbl

[19] Lin, C. H., Tan, B., Hsieh, P. J.: Application of the fuzzy weighted average in strategic portfolio management. Decision Sciences 36 (2005), 3, 489-511. | DOI

[20] Liu, F., Mendel, J. M.: Aggregation using the fuzzy weighted average as computed by the Karnik-Mendel algorithms. IEEE Trans. Fuzzy Systems 16 (2008), 1, 1-12. | DOI

[21] Liu, X., Mendel, J. M., Wu, D.: Analytical solution methods for the fuzzy weighted average. Inform. Sci. 187 (2012), 151-170. | DOI | MR | Zbl

[22] Pavlačka, O., Talašová, J.: Application of the Fuzzy Weighted Average of Fuzzy Numbers in Decision Making Models. In: New Dimensions in Fuzzy Logic and Related Technologies. Vol II. (M. Štěpnička,, V. Novák, and U. Bodenhofer, eds.) Proc. 5th EUSFLAT Conference, Ostravská univerzita, Ostrava 2007, pp. 455-462.

[23] Pavlačka, O., Talašová, J.: Fuzzy vectors as a tool for modeling uncertain multidimensional quantities. Fuzzy Sets and Systems 161 (11) (2010), 1585-1603. | DOI | MR | Zbl

[24] Pavlačka, O.: Modeling uncertain variables of the weighted average operation by fuzzy vectors. Inform. Sci. 181 (22) (2011), 4969-4992. | DOI | MR | Zbl

[25] Pavlačka, O.: Note on the lack of equality between fuzzy weighted average and fuzzy convex sum. Fuzzy Sets and Systems 213 (2013), 102-105. | DOI | MR | Zbl

[26] Ricci, R. G., Mesiar, R.: Multi-attribute aggregation operators. Fuzzy Sets and Systems 181 (2011), 1-13. | DOI | MR | Zbl

[27] Sachs, T., Tiong, R. L. K.: Quantifying qualitative information on risks: development of the QQIR method. J. Construction Engrg. Management-Asce 135 (2009), 1, 56-71. | DOI

[28] Talašová, J.: NEFRIT - Multicriteria Decision Making Based on Fuzzy Approach. Central Europ. J. Oper. Res. 8 (2000), 4, 297-319. | MR | Zbl

[29] Wang, Y. M., Elhag, T. M. S.: Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Systems Appl. 31 (2006), 2, 309-319. | DOI

[30] Wang, Y. M., Elhag, T. M. S.: On the normalization of interval and fuzzy weights. Fuzzy Sets and Systems 157 (2006), 2456-2471. | DOI | MR | Zbl

[31] Wei, C. C., Chang, H. W.: A new approach for selecting portfolio of new product development projects. Expert Systems Appl. 38 (2011), 1, 429-434. | DOI

[32] Wu, W. Y., Lin, C. H., Kung, J. Y., Lin, C. T.: A new fuzzy TOPSIS for fuzzy MADM problems under group decisions. J. Intelligent and Fuzzy Systems 18 (2007), 2, 109-115. | MR | Zbl

[33] Xu, Q., Ma, L., Nie, W. F., Li, P., Zhang, J. W., Sun, J. Z.: Adaptive fuzzy weighted average filter for synthesized image. In: Computational Science and Its Applications - ICCSA 2005, Part 3, Lecture Notes in Computer Science, vol. 3482, Springer-Verlag, Berlin 2005, pp. 292-298. | DOI

Cité par Sources :