Extension of VIKOR Method for Multi-Attribute Group Decision Making with Incomplete Weights

Article Preview

Abstract:

In this paper, we First utilize the induced interval-valued intuitionistic fuzzy hybrid averaging (I-IIFHA) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision makers into a collective interval-valued intuitionistic fuzzy decision matrix. Based on the basic ideal of traditional VIKOR method, we establish an optimization model to determine the weights of attributes. Then, calculation steps based on the collective interval-valued intuitionistic fuzzy decision matrix and traditional VIKOR method for solving the MAGDM problems with interval-valued intuitionistic fuzzy assessments and partially known weight information are given. Finally, a numerical example is used to illustrate the applicability of the proposed approach.

You might also be interested in these eBooks

Info:

* - Corresponding Author

[1] S. Opricovic, Multicriteria optimization of civil engineering systems, Faculty of Civil Engineering, University of Belgrade, Belgrade, Yugoslavia, (1998).

Google Scholar

[2] S. Opricovic, G.H. Tzeng, Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS, European Journal of Operational Research 156 (2004) 445-455.

DOI: 10.1016/s0377-2217(03)00020-1

Google Scholar

[3] M. Zeleny, Multiple criteria decision making, McGraw-Hill, New York, (1982).

Google Scholar

[4] S. Opricovic, G.H. Tzeng, A comparative analysis of the DEA-CCR model and the VIKOR method, Yugoslav Journal of Operations Research 18 (2008) 187-203.

DOI: 10.2298/yjor0802187o

Google Scholar

[5] M.T. Chu, J. Shyu, G.W. Tzeng, R. Khosla, Comparison among three analytical methods for knowledge communities group-decision analysis, Expert Systems with Applications 33 (2007) 1011-1024.

DOI: 10.1016/j.eswa.2006.08.026

Google Scholar

[6] S. Opricovic, A fuzzy compromise solution for multicriteria problems, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 15 (2007) 363-380.

DOI: 10.1142/s0218488507004728

Google Scholar