innovative q-rung orthopair fuzzy prioritized interactive aggregation operators to evaluate efficient autonomous vehicles for freight transportation

Road freight transport, in particular, is associated with a number of negative external factors, including environmental and health care concerns, as well as the excessive use of nonrenewable natural resources. in the metropolitan climate, urban freight transport has a particularly noticeable ecological footprint. this is the most pressing issue confronting all stake holders involved in urban freight transportation. in multi-criteria group decision-making (mcgdm) strategies, the lack of contact between membership degree (msd) and non-membership degree (nmsd) would be the basic factor for poor results in many mcgdm. to address these drawbacks, we define new aggregation operators (aos) methods based on generalized membership grades of q-rung orthopair fuzzy (q-rof) information, in this way, the input evaluation is interpreted in terms of q-rung orthopair fuzzy numbers (q-rofns). while interactive operators are well-known for interrelationship between generalized membership grades, prioritized operators are well-suited to exploit prioritized relationships among various criterion. based on the characteristics of such flexible operators, two novel hybrid aggregation operators are proposed named as &q-rung orthopair fuzzy prioritized interactive weighted averaging operator and the q-rung orthopair fuzzy prioritized interactive weighted geometric operator&.