Proportional distribution based Pythagorean fuzzy fairly aggregation operators with multi-criteria decision-making

Pythagorean fuzzy sets (PyFSs) are an essential tool for characterizing data in decision-making processes. In contrast to normal structures, PyFSs feature a sum of squares membership grades that is near unit interval, which increases uncertainty. Within environment, we intend build unique operational rules and aggregation operators (AOs) this proposed work. The work presents; notions, rules, proportionate notions establish fair remedy the degree (MSD) non-membership (NMSD) characteristics "Pythagorean numbers" (PyFNs) along with algorithms. Our AOs give more generalized, definitive, precise information than earlier methods. If decision-makers (DMs) have partial weight under PyFSs, then by combining AOs, one can solve "multi-criteria decision-making" (MCDM) problem applying To demonstrate applicability superiority our technique, present example illustrating efficacy suggested algorithm resolving issues, comparison has been presented existing approaches.