Development and improvement of ranking index in TOPSIS method with pticture fuzzy data
Subject Areas :
Vahide Hojjati NajafAbadi
1
,
reza maddahi
2
1 - Department of Mathematics, Computer Faculty, Najaf Abad Branch, Islamic Azad University, Najaf Abad, Iran
2 - Department of Mathematics, Computer Faculty, Najaf Abad Branch, Islamic Azad University, Najaf Abad, Iran
Keywords: TOPSIS, Fuzzy set, Intuitive Fuzzy set, Picture Fuzzy set,
Abstract :
Purpose: Development and improvement of ranking index in TOPSIS method with picture fuzzy data
Research methodology: In this papaer, the appropriate method for accessing and presenting information is the library method combined with technical engineering principles, analytical-experimental methods, and software implementation.
Findings: In this paper, constant value 1/2 was proved for L_i^- + L_i^+. The advantage of the proposed method is that reducing the MCDM problem from n dimensions to two dimensions makes the ranking easier. In fact, a new similarity index in the range of distance (L_i^- , L_i^+) uses fuzzification.
Originality/scientific added value: By solving an example with fuzzy numbers that is presented in the definition of visual fuzzy numbers in this paper, the necessary changes are made using Excel software and the distance to the ideal and anti-ideal state is calculated. Finally, a new ranking is determined.
A. De Luca, S. T. (1972). A definition of a nonprobabilistic entropy inthe setting of fuzzy sets theory. Inf. Control, 301-312.
Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy sets and Systems, 20, 87-96.
Atanassov, K. T. (1986). Intuitionistic Fuzzy Sets. Fuzzy Sets and Systems, 1-18.
C. L. Hwang, K. Y. (1981). Methods for multiple attribute decision making. Mult. attrib. Decis. Mak., 58-191, https://doi.org/10.1007/978-3-642-48318-9_3.
F. E. Boran, S. G. (2009). A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36(8), 11363-11368, https://doi.org/10.1016/j.eswa.2009.03.039.
G. R. Jahanshahloo, F. H. (2006). Extension of the TOPSIS method for decision-making problems with fuzzy data. Applied Mathematics and Computation, 181(2), 1544-1551, https://doi.org/10.1016/j.amc.2006.02.057.
Gandotra, S. N. (2021). Use of (R,S)-Norm concept and TOPSIS approach under picture fuzzy environment for application in multi criteria decision making issues. Materials Today: Proceedings, 307, https://doi.org/10.10.16/j.matpr.2021.03.307.
Hwang, C. a. (1981). Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey. New York: Springer-Verlag, https://doi.org/10.1007/978-3-642-48318-9_3.
Joshi, R. (2020). A nove decision-making method using R-Norm concept and VIKOR approach under picture fuzzy environment. Expert Syst. Appl., 147, https://doi.org/10.1016/j.eswa.2020.113228.
Kreinovich, B. C. (2013). Picture Fuzzy Sets-a new concept for conputational intelligence problems. Departmental Technical Reports, 809, 1-6, https://scholarworks.utep.edu/cs_techrep/809.
LA.Zadeh. (1965). Fuzzy sets. inf. control, 338-353, https://doi.org/10.1016/S0019-9958(65)90241-X.
R. Joshi, S. K. (2016). (R-S)- norm information measure and a relation between coding and questionnaire theory, open Syst. Inf. Dyn., 23, https://doi.org/10.1142/S1230161216500153.
S.A. Sadabadi, A. H.-V. (2022). An Improved Fuzzy TOPSIS Method With a New Ranking Index. World Scientific, 615-641, https://doi.org/10.1142/S0219622021500620.
Son, L. H. (2016). Generalized picture distance measure and applications to picture fuzzy clustering. ELSEVIER, 284-295, https://doi.org/10.1016/j.asoc.2016.05.009.
Tzou, G. H. (1983). Fuzzy Multiple Objective Decision Making: Methods and Applications. Fuzzy Sets and Systems, 11.
V.Kreinovich, B. (2014). Picture fuzzy sets. J. Comput Science and Cybernetics, 409-416, https://doi.org/10.15625/1813-
9663/30/4/5032. Wei, G. (2016). Peacture fuzzy cross-entropy for multiple attribute decision making problems. J. Bus. Econ. Manag, 15, 491-502, https://doi.org/10.3846/16111699.2016.1197147.