On weakly prioritized multicriteria decision analysis with interval-valued hesitant fuzzy information

Hesitant fuzzy sets (HFSs) is a powerful tool in modelling and managing uncertainty of real-world decision-making problems. As a generalization of HFSs, interval-valued hesitant fuzzy sets (IVHFSs) can model preferences of decision makers with several possible interval values. Within the framework of IVHFSs, this work develops a weakly prioritized multicriteria decision analysis method for addressing problems where there exists a weakly ordered prioritization relationship over criteria. The prioritization relationship between criteria is characterized by the interval-valued hesitant fuzzy weights that are associated with criteria dependence on the satisfaction of the higher priority criteria. First, a novel prioritized scoring operator is developed to aggregate interval-valued hesitant fuzzy information coming from simultaneous sources with different priority levels. Then, we present an operator-based decision analysis method to address multicriteria decision making problems with weakly prioritized preferences over criteria. Finally, an illustrative example of global mineral investment is provided to show the application of the proposed method. Comparison analyses with existing prioritized multicriteria decision analysis methods show that the proposed method can effectively characterize weakly ordered prioritization relationship over the criteria as well as that it can avoid information loss in eliciting the final recommendations by introducing uncertain weights.