5. Consensus Model-Based Hesitant Fuzzy Multiple Criteria Group Decision Analysis

The MCGDM is an important research topic in decision theory. Many useful methods have been proposed to solve various MCGDM problems, but very few methods simultaneously take them into account from the perspectives of both the ranking and the magnitude of decision data, especially for the hesitant fuzzy situations. The purpose of this chapter is to develop a consensus model-based hesitant fuzzy group decision making method to handle hesitant fuzzy MCGDM problems by simultaneously taking into account such two aspects of hesitant fuzzy decision data. Firstly, an ordinal consensus index is presented for measuring the consensus among individual experts’ opinions from the perspective of the ranking of decision information. Then, a cardinal consensus index is presented for measuring the consensus among individual experts’ opinions from the perspective of the magnitude of decision information. Afterwards, a linear programming model to derive the weights of experts is constructed according to the idea that the expert with a larger consensus should be assigned a larger weight. Finally, the relative closeness indices of alternatives are determined and the ranking of alternatives is identified.