Multiattribute decision making based on non-linear programming methodology with hyperbolic function and interval-valued intuitionistic fuzzy values

Abstract

In this paper, we present a novel multiattribute decision making (MADM) method based on the non-linear programming (NLP) methodology with the hyperbolic tangent function and interval-valued intuitionistic fuzzy values (IVIFVs). Both the attributes’ weights and the decision matrix (DM) are expressed by IVIFVs. First, the proposed MADM method constructs the transformed decision matrix (TDM) of the DM. Then, it constructs a NLP model with the hyperbolic tangent function to get the optimal weights of the attributes. Then, it uses the interval-valued intuitionistic fuzzy weighted averaging (IVIFWA) operator to calculate the weighted evaluating IVIFVs of the alternatives. Finally, it uses Wang et al.’s method (2009) for comparing IVIFVs to obtain the preference order (PO) of the alternatives. It can conquer the shortcomings of Chen and Huang's MADM method (2017).