New development of the neutrosophic fuzzy soft set framework using several aggregation operator techniques

Ahmad A. Abubaker; Abdallah Al-Husban; Murugan Palanikumar; R. Uma

Authors

Ahmad A. Abubaker Faculty of Computer Studies, Arab Open University, Saudi Arabia;
Abdallah Al-Husban Department of Mathematics, Faculty of Science and Technology, Irbid National University, P.O. Box: 2600 Irbid, Jordan;
Murugan Palanikumar Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai-602105, India;
R. Uma Department of Mathematics, Roever Engineering College, Perambalur;

Keywords:

: Soft set, neutrosophic fuzzy soft set, decision making, aggregation operator

Abstract

The soft set is a general mathematical technique for dealing with uncertainty. For this reason,
the soft set theory has attracted a lot of attention from academics, particularly in the context of managing
uncertainty in decision-making scenarios. However, since the membership degrees of the components that
comprise the universe set in the theory are only stated with 0 or 1, it is difficult to precisely characterize the
uncertainty. The interval valued Pythagorean neutrosophic soft set (IVPNSS) is an extension of the Pythagorean
fuzzy soft set and interval valued neutrosophic soft set. Based on the aggregating method, we talk about
aggregated operations for IVPNSS over a scoring function. to determine which choice is optimal. We use
practical problems to ascertain how a buyer must decide which motorcycle to purchase. For instance, a car
company produces ten various kinds of motorcycles, and a set of criteria includes things like fuel tank capacity,
improved style, higher mileage, and durability. In the end, these algorithms were compared, and it was made
obvious how they differed from earlier algorithms that had been suggested. To illustrate the comparison study,
sensitivity analysis and the viability of our suggested technique are both carried out. Decision makers will find
the results very helpful in effectively handling contradicting and unclear information

DOI: 10.5281/zenodo.17041979