Order-α_cq divergence measures and aggregation operators based on complex q-rung orthopair normal fuzzy sets and their application to multi-attribute decision-making

Complex q-rung orthopair fuzzy set (CQROFS) contains the grade of supporting and the grade of supporting against in the form of polar coordinates belonging to unit disc in a complex plane and is a proficient technique to address awkward information, although the normal fuzzy number (NFN) examines normal distribution information in anthropogenic action and a realistic environment. Based on the advantages of both notions, in this manuscript, we explored the novel concept of a complex q-rung orthopair normal fuzzy set (CQRONFS) as an imperative technique to evaluate unreliable and complicated information. Some operational laws based on CQRONFSs are also explored. Additionally, some distance measures, called complex q-rung orthopair normal fuzzy generalized distance measure (CQRONFGDM), complex q-rung orthopair normal fuzzy symmetric distance measure (CQROFNFSDM), two types of complex q-rung orthopair normal fuzzy order-divergence measures (CQRONFODMs), and their special cases are discussed. Moreover, weighted averaging, weighted geometric, generalized weighted averaging, and generalized weighted geometric operators based on CQRONFSs are also presented. In last, we solved a numerical example of a multi-attribute decision-making (MADM) problem is shown to justify the proficiency of the presented operators. The advantages, comparative and sensitive analyses are used to express the efficiency and flexibility of the explored approach.