Application of Single-Valued Neutrosophic Power Maclaurin Symmetric Mean Operators in MADM

Abstract

The power average (PA) operator, at first developed by Yager, which can diminish the pessimistic influence of uncomfortable measurement values on the final decision results. The Maclaurin symmetric mean (MSM), initially developed by Maclaurin, which can take the interrelationship between multi-input parameters. However, in real world the decision making problems (DMPs) are flattering progressively complex, and it is necessary to diminish the pessimistic influence of embarrassed assessment values and mull over the interrelationship between multi-opinions at a time. In this article, to handle such situation, we merge the PA operator with MSM and inflated them to grip single valued neutrosophic (SVN) information, and anticipated the perception of SVN power MSM (SVNPMSM) operator, the weighted SVNPMSM (WSVNPMSM) operator, the SVN dual power MSM (SVNDPMSM) operator and the weighted SVN dual power MSM (WSVNDPMSM) operators. Then, several basic qualities of the anticipated aggregation operators (AOs) are examined. Additionally, based on these anticipated AOs, we build up a new approach to multiple-attribute decision-making (MADM) under SVN environment. Finally, an example is illustrated to show the validity and practicality of the anticipated approach by differentiating with the other presented methods.