Abstract
Abstract A new method is developed to solve multi-attribute group decision making (MAGDM) problem in which the attribute values, attribute weights and expert weights are all in the form of 2-tuple linguistic information. First, the operation laws for 2-tuple linguistic information are defined and the related properties of the operation laws are studied. Then, some new hybrid geometric aggregation operators with 2-tuple linguistic information are developed, involving the 2-tuple hybrid weighted geometric average (THWAG) operator, the 2-tuple hybrid linguistic weighted geometric average (T-HLWG) operator and the extended 2-tuple hybrid linguistic weighted geometric average (ET-HLWG) operator. These hybrid geometric aggregation operators generalize the existing 2-tuple linguistic geometric aggregation operators and reflect the important degrees of both the given 2-tuples and the ordered positions of the 2-tuples. In the proposed decision method, using the ET-HLWG operators the individual overall preference v...
Highlights
Multi-attribute group decision making (MAGDM) problems with linguistic information arise from a wide range of real-world situations (Jiang et al.[1]; Herrera and Herrera-Viedma[2]; Parreiras et al.[3])
Wei and Lin[20] and Wei[22] developed grey relational analysis (GRA) MAGDM methods based on 2-tuple linguistic information
The extended 2-tuple ordered weighted geometric (ET-OWG) operator is a special case of the tuple hybrid linguistic weighted geometric average (T-HLWG) operator
Summary
Multi-attribute group decision making (MAGDM) problems with linguistic information arise from a wide range of real-world situations (Jiang et al.[1]; Herrera and Herrera-Viedma[2]; Parreiras et al.[3]). This paper develops some new hybrid geometric aggregation operators with 2-tuple linguistic information and proposes a new method for MAGDM problems with 2-tuple linguistic assessments. (ii) The hybrid aggregation operators can reflect the important degrees of both the given 2-tuples and the ordered positions of the 2-tuples They are usually used to integrate the individual overall preference values of alternatives into the collective ones of alternatives. The MAGDM method of Wei[8] can not deal with the case that the weight information of attributes and experts takes the form of the 2-tuples This case may appear in some real-life decision problems (see Section 5). These new hybrid geometric aggregation operators with 2-tuple linguistic information proposed in this paper can effectively overcome this drawback.
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