An interaction consensus in group decision making under distributed trust information

A theoretical interaction consensus model in group decision making with distributed linguistic trust information is proposed. To do that, the concept of distributed linguists trust function (DLTF) is defined, and then the associated operational laws and aggregation operations are explored. Combining the expectation degree and uncertainty degrees, a ranking method for distributed linguists trust function is proposed. To identify the inconsistent experts, three levels of consensus degree with DLTF are calculated. After that, a novel feedback mechanism is activated to generate recommendation advices for the inconsistent experts to higher consensus degree. Therefore, the inconsistent experts are able to reach the threshold value of group consensus. Finally, after consensus has been achieved, a ranking order relation for distributed linguists trust functions is constructed to select the most appropriate
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