The optimization-based aggregation and consensus with minimum-cost in group decision making under incomplete linguistic distribution context

In real decision making, due to the limitation of knowledge, problem complexity and time pressure, it is natural that decision makers express their opinions with incomplete linguistic information. This paper developed a novel consensus model for group decision making (GDM) with incomplete linguistic distribution assessments (ILDAs). Firstly, we defined the concept of ILDAs and the consensus measure for GDM with ILDAs. Then, we presented a consensus-oriented aggregation model, which can obtain a collective opinion with maximum consensus, and further developed a minimum-cost consensus model with variable unit consensus cost. Following this, based on the proposed aggregation and consensus models, we proposed a novel consensus reaching process for GDM with ILDAs. Finally, a numerical example is conducted to demonstrate the validity of the proposed consensus reaching process.