Abstract
With respect to multi-attribute group decision-making (MAGDM) problems, where attribute values take the form of interval grey trapezoid fuzzy linguistic variables (IGTFLVs) and the weights (including expert and attribute weight) are unknown, improved grey relational MAGDM methods are proposed. First, the concept of IGTFLV, the operational rules, the distance between IGTFLVs, and the projection formula between the two IGTFLV vectors are defined. Second, the expert weights are determined by using the maximum proximity method based on the projection values between the IGTFLV vectors. The attribute weights are determined by the maximum deviation method and the priorities of alternatives are determined by improved grey relational analysis. Finally, an example is given to prove the effectiveness of the proposed method and the flexibility of IGTFLV.
Highlights
Multi-attribute group decision-making (MAGDM) refers to the decision process of selecting optimal alternatives based on multiple attributes
The attribute weights are determined by the maximum deviation method
This paper uses the projection value between interval grey trapezoid fuzzy linguistic variables (IGTFLVs) vectors to express the similarity between group evaluation and individual evaluation
Summary
Multi-attribute group decision-making (MAGDM) refers to the decision process of selecting optimal alternatives based on multiple attributes. Wang and Wang [8] defined the grey and fuzzy parts as interval numbers, and the method of aggregating information utilized an ordered weighted averaging (OWA) operator. Wei [16] utilized the 2-tuple linguistic terms to express the fuzzy part and proposed a multi-attribute decision-making (MADM) method based on grey relation analysis. In order to better express fuzzy information, Liu and Wang [19] defined the concept of generalized interval-valued trapezoidal fuzzy numbers, the operational rules, the distance between generalized interval-valued trapezoidal fuzzy numbers, and proposed several weighted geometric aggregation operators. This paper uses the projection value between IGTFLV (interval grey trapezoid fuzzy linguistic variables) vectors to express the similarity between group evaluation and individual evaluation.
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