q-Rung orthopair fuzzy hypersoft ordered aggregation operators and their application towards green supplier

Green Supply Chain Management (GSCM) is essential to ensure environmental compliance and commercial growth in the current climate. Businesses constantly look for fresh concepts techniques ensuring sustainability. To keep up with new trends concerns related company management procedures, Supplier Selection (GSS) criteria are added traditional supplier selection processes. This study aims identify general provide a framework that can assist decision-makers choosing prioritizing appropriate green selection. The development implementation of decision support systems aimed solve these difficulties at rapid rate. In order manage inaccurate data simulate decision-making problems. Fuzzy sets introduced by Zadeh, useful technique handle imperfectness uncertainty different Although fuzzy incomplete information real worlds problems, but its cannot all type such as indeterminate data. Therefore extensions intuitionistic fuzzy, pythagorean q-rung orthopair address problems considering membership non-membership grade. However, have some shortcomings handling sub-attributes. overcome this Khan et al. developed structure hypersoft combining sets. A remarkable beneficial research work done field sets, then we think about application. paper, use multi-criteria For this, present aggregation operator (MCDM) (q-ROFH) information, known ordered weighted geometric operator. Since vagueness an unavoidable feature proposed be tool making uncertain environment. Further, expert opinions were investigated using technique, which helped interrelationship causal preference evaluation aspects used operators. Finally, numerical example method task presented.