Independent hesitant fuzzy group decision making methods with application to person and post matching

This paper aims to study an effective group decision making (GDM) method for dealing with the hesitant fuzzy context and apply it to solving person and post matching problem. We studied the hesitant fuzzy information aggregation problem in two folds, 1) consider confidence levels of the decision makers; 2) consider different priority levels of the decision makers or criteria. Firstly, we propose some Hamacher based aggregation operators considering different confidence levels and Hamacher based aggregation operator considering different prioritized levels. Then, special cases of these operators and numerical examples are analyzed. Finally, we propose a new GDM method using these operators and applied to person and post matching problem.