A semantic model for computing with flexible linguistic expressions and the application in MCGDM

The flexible linguistic expression (FLE) is a generalization of the hesitant fuzzy linguistic term set and linguistic distribution. An FLE expresses a preference in the form of hesitant fuzzy linguistic term sets with the symbolic proportions. The existing studies mainly utilize a symbolic way to compute with FLEs. To provide a semantic model for computing with FLEs, this paper proposes to represent an FLE with a triangular fuzzy number. Two approaches based on the maximum entropy principle are introduced to compute the triangular fuzzy membership functions for complete and incomplete FLEs. A multi-criteria group decision making (MCGDM) model based on FLEs is then proposed, in which the criteria are divided into different subsets of sub-criteria which are selected for different decision makers. A consensus reaching process is introduced to improve consensus of the decision makers by modifying weights of the sub-criteria. Finally the MCGDM model is applied to an autonomous driving evaluation problem.

Automated summary

The paper proposes representing FLEs with triangular fuzzy numbers and introduces two approaches based on the maximum entropy principle to compute triangular fuzzy membership functions for complete and incomplete FLEs. A multi-criteria group decision making (MCGDM) model based on FLEs is then proposed, with a consensus reaching process introduced to improve decision makers' consensus. The MCGDM model is applied to an autonomous driving evaluation problem in the end.