ATTRIBUTES WEIGHT DETERMINATION FOR INTERVAL VALUED INTUITIONISTIC FUZZY MULTIPLE ATTRIBUTE GROUP DECISION MAKING PROBLEMS

In this paper, the Multiple Attribute Group Decision Making (MAGDM) problems are investigated in which all the information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices, and the information about attribute weights is partially known. The first model is based on the attribute weights calculated from partially known information using the score function of Xu, (2007) and the second model is based on the Gaussian distribution function for calculating the completely unknown attribute weights. The interval-valued intuitionistic fuzzy ordered weighted averaging (IIFOWA) operator is utilized to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the obtained attribute weights and the interval-valued intuitionistic fuzzy hybrid averaging (IIFHA) operator to fuse the interval-valued intuitionistic fuzzy information in the collective interval-valued intuitionistic fuzzy decision matrix to get the overall interval valued intuitionistic fuzzy values of alternatives, and then rank the alternatives according to the correlation coefficients between the Interval Valued Intuitionistic Fuzzy Numbers (IVIFNs) and select the most desirable one(s). Finally, numerical examples are used to illustrate the effectiveness of the proposed approaches