We introduce a new type of fuzzy preference structure, called interval-valued hesitant preference relations, to describe uncertain evaluation information in group decision making (GDM) processes. Moreover, it allows decision makers to offer all possible interval values that are not accounted for in current preference structure types when one compares two alternatives. We generalize the concept of hesitant fuzzy set (HFS) to that of interval-valued hesitant fuzzy set (IVHFS) in which the membership degrees of an element to a given set are not exactly defined, but denoted by several possible interval values. We give systematic aggregation operators to aggregate interval-valued hesitant fuzzy information. In addition, we develop an approach to GDM based on interval-valued hesitant preference relations in order to consider the differences of opinions between individual decision makers. Numerical examples are provided to illustrate the proposed approach.

Interval-valued hesitant preference relations and their applications to group decision making

Public acceptance and preferences related to renewable energy and grid expansion policy: Empirical insights for Germany

Uncertain linguistic Bonferroni mean operators and their application to multiple attribute decision making

An outranking approach for multi-criteria decision-making with hesitant fuzzy linguistic term sets

In this paper, we investigate the uncertain multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Motivated by the idea of prioritized aggregation operators (Yager 2008), we develop some prioritized aggregation operators for aggregating uncertain information, and then apply them to develop some models for uncertain multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Finally, a practical example about talent introduction is given to verify the developed approach and to demonstrate its practicality and effectiveness.

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Tien-Chin Wang

Papers

Multi-criteria decision making with fuzzy linguistic preference relations