A personalized individual semantics model for computing with linguistic intuitionistic fuzzy information and application in MCDM

Abstract

Abstract This paper develops a personalized individual semantics (PISs) model for computing with linguistic intuitionistic fuzzy information and applies to evaluating different brands of mobile phones. First, considering that a linguistic term means different things to different decision-makers, a consistency-driven optimization model for checking the additive consistent linguistic intuitionistic fuzzy preference relations (LIFPRs) is constructed by considering the PISs of a decision maker. Besides, several optimization models is built to determine the PISs of linguistic terms in LIFPRs and obtain the acceptable additive consistent LIFPRs. Second, a new definition of Hamming distance between linguistic intuitionistic fuzzy numbers (LIFNs) is developed by considering the PISs of a decision maker, and several of its desirable properties are discussed. Then, the method of deriving the weight vectors of criteria is calculated based on the proposed distance measure. Subsequently, a framework of group decision making process with LIFPRs is offered, and the application of the proposed method is illustrated by using a multi-criteria decision-making problem about evaluating different brands of mobile phones. Finally, the comparative analysis is conducted to show the feasibility of proposed group decision-making method.