Interval-valued intuitionistic neutrosophic hypersoft TOPSIS method based on correlation coefficient

Abstract

In multi-criteria decision-making problems, we may have to deal with numbers that are in interval forms, like those of membership, non-membership grades and indeterminacy grades representing unique attributes of elements. When decision-makers come across such an environment, the decisions are harder to
make and the most significant factor is that we need to combine these interval numbers to generate a single real number, which can be done using aggregation operators or score functions. To overcome this hindrance, we introduce the notion of interval-valued intuitionistic neutrosophic hypersoft set. This eventually helps the decision-maker to collect the data with no misconceptions. The primary aim of this study is to establish some operational laws for interval-valued intuitionistic neutrosophic hypersoft set. Also, we present the fundamental properties of two aggregation operators, interval-valued intuitionistic neutrosophic weighted average and interval-valued intuitionistic neutrosophic weighted geometric operators. Also, we propose an algorithm for the
technique of order of preference by similarity to ideal solution (TOPSIS) method based on correlation coefficients to choose a suitable employee among the alternative using Leipzig leadership model in an organization for an upcoming new project. Finally, we present a comparative study with existing similarity measures to show the effectiveness of the proposed method.