Robust QSVN Soft Aggregation Operators in Rural Healthcare Problem

Abstract

Molodtsov developed Soft set theory (SST) which is a useful transition of Fuzzy set theory. This theory is applied in a broad mathematical structure for dealing with uncertainties. The primary goal of this research is to establish the groundwork in the light of SST for the development of a quadripartitioned single valued neutrosophic (QSVN) soft tool that takes uncertainty in numerous problems into account. In this study we have defined two newly hybrid aggregation operators (AOs) namely QSVN soft (QSVNS) weighted arithmetic average (QSVNSWAA) Operator and QSVN soft  weighted geometric average (QSVNSWGA) operator on QSVNS numbers. Also in order to aggregate various QSVNS input arguments in a QSVNS environment, two QSVNS numbers have also been compared using the QSVNSWAA and QSVNSWGA operators. Further this article carefully reviews the basic algebraic operations of these newly introduced AOs. In the end, a rural healthcare problem is given to assess the viability and usefulness of the suggested work.