Hierarchical clustering of interval-valued intuitionistic fuzzy relations and its application to elicit criteria weights in MCDM problems

The paper aims to apply the (α~ , β~) -cuts and the resolution form of the interval-valued intuitionistic fuzzy (IVIF) relations to develop a procedure for constructing a hierarchical clustering for IVIF max–min similarity relations. The advantage of the proposed scheme is illustrated in determining the criteria weights in multi-criteria decision making (MCDM) problems involving IVIF numbers. The problem of finding the criteria weights is of critical interest in the domain of MCDM problems. A complete procedure is drawn to generate criteria weights starting from the criteria-alternative matrix of the MCDM problem with entries provided by a decision maker as IVIF numbers. © 2016, Operational Research Society of India.