Correlation coefficient of interval-valued intuitionistic fuzzy sets and its application to multiple attribute group decision making problems

  • Authors:

  • Dong Gun Park;Young Chel Kwun;Jin Han Park;Il Young Park

  • Affiliations:

  • Department of Mathematics, Dong-A University, Pusan 604-714, South Korea;Department of Mathematics, Dong-A University, Pusan 604-714, South Korea;Division of Mathematical Sciences, Pukyong National University, Pusan 608-737, South Korea;Division of Mathematical Sciences, Pukyong National University, Pusan 608-737, South Korea

  • Venue:
  • Mathematical and Computer Modelling: An International Journal
  • Year:
  • 2009

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Abstract

In this paper, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFN), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator 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 score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and then we use the obtained attribute weights and the interval-valued intuitionistic fuzzy weighted geometric (IIFWG) 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 IVIFNs and select the most desirable one(s). Finally, a numerical example is used to illustrate the applicability of the proposed approach.