Multi-attribute Group Decision-Making Based on Pythagorean Fuzzy Rough Set and Novel Schweizer-Sklar T-norm and T-conorm

Abstract

The Pythagorean fuzzy rough set (PyFRS) is a robust framework that plays a vital role in reducing the uncertainty from the extracted information from real-life scenarios. In this article, we proposed some aggregation operators (AOs) based on Schweizer-Sklar t-norm (SSTrM) and Schweizer-Sklar t-conorm (SSTCrM). These AOs include Pythagorean fuzzy rough (PyFR) Schweizer-Sklar weighted averaging (PyFRSSWA) and PyFR Schweizer-Sklar (SS) weighted geometric (PyFRSSWG) operators to deal with the information in the form of PyFR values (PyFRVs). The basic properties of the developed AOs are investigated and then applied to the multi-attribute group decision-making (MAGDM) problem. The variation of the obtained results is obtained by changing the values of the involved parameter in SSTrM and SSTCrM. Additionally, the obtained results are compared with those obtained by existing AOs. Furthermore, all the observations and results are presented graphically.