novel decision-making framework based on complex q-rung orthopair fuzzy information

Assessing uncertainty in decision-making is a major challenge for decision-makers (dms), and the q-rung orthopair fuzzy set (q-rofs) as the direct extension of intuitionistic fuzzy set (ifs) and pythagorean fuzzy set (pfs) play a crucial role in this aspect. the complex q-run orthopair fuzzy set (cq-rofs) is a strong tool to deal with imprecision, vagueness, and fuzziness by expanding the scope of membership degree (md) and non-membership degree (nmd) of q-rofs from real to complex unit disc. in this paper, we develop some new cq-rof hamacher aggregation operators (aos), i.e., the cq-rof hamacher weighted averaging (cq-rofhwa) operator, the cq-rofh weighted geometric (cq-rofhwg) operator, the cq-rofh ordered weighted averaging (cq-rofhowa) operator, and the cq-rofh ordered weighted geometric (cq-rofhowg) operator. subsequently, we establish a novel cq-rof graph framework based on the hamacher operator called cq-rofh graphs (cq-rofhgs) and evaluate its energy and randic energy. in particular, we compute the energy of a splitting cq-rofhg and shadow cq-rofhg. further, we describe the notions of cq-rofh digraphs (cq-rofhdgs). moreover, an algorithm is given to solve multiple attribute group decision-making (magdm) problems and the main steps are discussed clearly. finally, a numerical instance related to the facade clothing systems (fcs) selection is presented to show the eectiveness of the developed concepts in decision-making circumstances. in order to verify the eectiveness of our proposed scheme, a comparative analysis with previous approaches is provided.