Multi-attribute Group Decision-Making Method Based on Cloud Distance Operators With Linguistic Information

Linguistic terms can easily express the qualitative information given by decision makers, but such a qualitative concept cannot be directly calculated like exact number. Thus, it needs to be translated to a quantitative concept. The cloud model can do the transformation well which has the advantage of describing the randomness and fuzziness of qualitative concepts synthetically. The distance operator is good at indicating internal relationship between values and reflecting the degree of deviation. Therefore, in this paper, we firstly introduce the conversion method from linguistic terms to cloud model, then propose a series of cloud distance aggregation operators such as cloud weighted averaging distance operator, cloud weighted geometric averaging distance operator, and cloud generalized weighted averaging distance operator (CGWAD), and prove some desired properties. Further, we develop a group decision-making method based on the CGWAD operator in which the TOPSIS method is extended to rank those alternatives. Finally, a numerical example is given to verify the practicability of the newly developed method.