Scoring rule and its application in intuitionistic fuzzy parameterized soft set-based decision-making problem

There is an importance of multi-criteria group decision-making (MCGDM) problems based on soft set theory in decision analysis. This article focuses on MCGDM problems based on intuitionistic fuzzy parameterized soft sets (IFPSS) structure. Our goal in decision-making is to select an object by verifying all the parameters. Fuzzy ranking is one of the essential critical tools used in the MCGDM process. The ranking system plays a vital role in the comparison of Intuitionistic fuzzy numbers (IFN) in MCGDM, like fuzzy numbers. However, most of the ranking methods on IFN mentioned in the literature have some limitations. By addressing the limitations of existing score functions and proposing a new and improved method for ranking IFNs, this article can make a significant contribution to the field of MCDM and decision-making under uncertainty. We have also introduced a new similarity measure of two intuitionistic fuzzy soft sets (IFSS). Using the concept of scoring rule, we have defined the reduced FP-soft set of an IFPSS. Additionally, we have calculated the adequate standard of a decision-maker in MCGDM problems under the IFPSS environment. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.