A novel technique for multiple attribute group decision making in interval-valued hesitant fuzzy environments with incomplete weight information

We propose a new technique for handling multiple attribute group decision making (MAGDM) problems in interval-valued hesitant fuzzy (IVHF) environments with imperfect weight information. Firstly, the quadratic programming model is given to acquire the weights of decision makers by utilizing maximum group consensus between individual and group IVHF decision matrices. Then, the maximum deviation method is employed to build an optimum model, where the best weights for attributes are obtained. Subsequently, an IVHF–TOPSIS approach is developed to obtain a solution that simultaneously has the smallest distance from the IVHF-positive ideal solution (IVHFPIS) and the largest distance from the IVHF-negative ideal solution (IVHFNIS). Ultimately, the novel method is verified with an investment example.