q-Rung Orthopair Probabilistic Hesitant Fuzzy Rough Aggregation Information and Their Application in Decision Making

The core contribution of this study is to develop a novel generalized idea q-rung orthopair probabilistic hesitant fuzzy rough set (q-ROPHFRS) which hybrid structure the set, and set. q-ROPHFRS covers positive negative membership grades in form information address uncertainties real-world decision-making problems. This paper proposes list averaging/geometric aggregation operators handle uncertainty effectively reliably aggregate uncertain under q-ROPHFRSs. Several interesting elementary properties have been investigated. Furthermore, multi-attribute approach based on proposed presented. Finally, numerical application regarding selecting medical oxygen supplier hospital presented illustrate consistency developed technique. comparison technique with TOPSIS shows that multi-criteria methodology reliable effective addressing