The \(p,q-\) quasirung orthopair fuzzy sets represent an innovative advancement in fuzzy set theory, addressing the constraints inherent in \(q-\) rung orthopair fuzzy sets. This new extension has gained considerable traction in multi-criteria group decision-making (MCGDM) scenarios. The Combinative Distance-based Assessment (CODAS) method is designed to enhance the multi-criteria selection process by maximizing both Euclidean and Taxicab distances relative to negative ideal solutions. In the literature, different extensions are proposed. However, these extensions are unable to address situations where decision makers may employ varying term levels for membership degrees. To bridge this gap, this paper enhances the traditional CODAS method by incorporating \(p,q-\) quasirung orthopair fuzzy ( \(p,q-\) QOF) numbers to effectively solve multi-criteria group decision-making (MCGDM) problems with incomplete weight information. The proposed CODAS approach enables decision makers to set distinct term levels (p and q) for membership and non-membership, enhancing evaluation precision. To illustrate the application of the proposed approach, a numerical example pertaining to retail location selection is presented. The comparative study demonstrates the superiority of the proposed approach over several relevant methods. In addition, a sensitivity analysis of the proposed CODAS method, conducted by varying the criteria weights, reveals a high degree of stability in the results.
