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Personalized individual semantics (PIS) exist widely in our daily life, and it means that different people have different understandings regarding the same word. In decision making, decision makers are accustomed to express their preferences using a linguistic way, and it is naturally that the PIS will influence the decision result in the linguistic decision making. In this paper, we propose a PIS-based MAGDM framework for multiple attribute group decision making (MAGDM) problems with the linguistic preference information on alternatives. In the novel framework, a two-stage based optimization model is constructed to deal with PIS by minimizing the deviation between objective preference information (i.e., multiple attribute decision matrix) and subjective preference information (i.e., linguistic preference relations over alternatives), and this optimization model is then transformed into a linear programming model that can be easily solved. Based on this, decision makers’ linguistic preference information can be transformed into numerical preference information for implementing the computation process. By fusing objective and subjective preference information, the collective solution of MAGDM problem can be obtained. The numerical and simulation experiments are conducted to verify the effectiveness of the proposal.

Personalized individual semantics based approach to MAGDM with the linguistic preference information on alternatives