JZUS - Journal of Zhejiang University SCIENCE

Journal of Zhejiang University SCIENCE A 2005 Vol.6 No.1 P.27-31

http://doi.org/10.1631/jzus.2005.A0027

The construction and combined operation for fuzzy consistent matrixes*

Author(s): Min Yao¹, Bin Shen¹, Jian-hua Luo²
Affiliation(s): 1. School of Computer Science, Zhejiang University, Hangzhou 310027, China; more
Corresponding email(s): myao@zju.edu.cn
Key Words: Fuzzy consistent matrix, Fuzzy consistent relation, Compound operation

Share this article to： More <<< Previous Article \|Next Article >>>

Abstract: Fuzziness is one of the general characteristics of human thinking and objective things. Introducing fuzzy techniques into decision-making yields very good results. fuzzy consistent matrix has many excellent characteristics, especially center-division transitivity conforming to the reality of the human thinking process in decision-making. This paper presents a new approach for creating fuzzy consistent matrix from mutual supplementary matrix in fuzzy decision-making. At the same time, based on the distance between individual fuzzy consistent matrix and average fuzzy consistent matrix, a kind of combined operation for several fuzzy consistent matrixes is presented which reflects most opinions of experienced experts. Finally, a practical example shows its flexibility and practicability further.

References

[1] Fan, Z.P., Ma, J., Zhang, Q., 2002. An approach to multiple attribute decision making based on fuzzy preference information on alternatives. Fuzzy Sets and Systems, 131:101-106.

[2] Herrera, F., Lopez, E., Rodirguez, M.A., 2002. A linguistic decision model for promotion mix management solved with genetic algorithms. , Fuzzy Sets and Systems, 47-61. :47-61.

[3] Li, H.J., 2001. Application of three standard degree method in group comparison and fuzzy comparison. System Engineering−. Theory and Practice, (in Chinese),21(7):87-91.

[4] Niskanen, V.A., 2002. A soft multi-criteria decision-making approach to assessing the goodness of typical reasoning systems based on empirical data. Fuzzy Sets and Systems, 131:79-100.

[5] Smolikova, R., Wachowiak, M.P., 2002. Aggregation operators for selection problems. Fuzzy Sets and Systems, 131:23-34.

[6] Wang, P.Z., Li, H.X., 1996. Fuzzy System Theory and Fuzzy Computers, (in Chinese), Science Press, Beijing,:

[7] Williams, J., Steele, N., 2002. Difference, distance and similarity as a basis for fuzzy decision support based on prototypical decision classes. Fuzzy Sets and Systems, 131:35-46.

[8] Xu, Z.S., 1999. Research on the relation of two scales in AHP. System Engineering−. Theory and Practice, (in Chinese),19(7):56-60.

[9] Yao, M., Huang, Y.J., 1998. Fuzzy consistent relation and Decision making. Journal of Systems Engineering and Electronics, 9(2):14-18.

[10] Zhang, J.Z., 2000. Fuzzy analytical Hi process. Fuzzy System and Mathematics, (in Chinese),14(2):80-88.

[11] Zhou, D., Ma, J., Turban, E., Bolloju, N., 2002. A fuzzy set approach to the evaluation of journal grades. Fuzzy Sets and Systems, 131:63-74.

Similar articles

- Go to

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

References