Reliability assessment of refined single-valued neutrosophic data with application in multi-criteria decision-making

Abstract

The refined single-valued neutrosophic set (RSVNS) has been extensively validated for its effectiveness in addressing complex multi-criteria decision-making (MCDM) problems. Unlike fuzzy sets and similar
sets, RSVNS includes a larger number of membership functions, making it especially capable of handling complex evaluation criteria within the decision-making framework. Therefore, this study presents a methodology
for the reliability assessment of data within refined single-valued neutrosophic numbers, along with a technique
for calculating the weighted average of a set of these numbers. The study then applies this methodology to a
MCDM problem using the similarity measure of RSVNS. By assessing each alternative’s similarity to the ideal
solution, it becomes possible to rank all alternatives and identify the most optimal choice. A real-world example
involving the selection procedure among various construction projects is studied to examine the effectiveness of
the proposed method. Furthermore, a comparative analysis has also been carried out to compare the reliability
and preference ranking of several alternatives derived using both the methodology considered and the existing
one.

DOI: 10.5281/zenodo.17041912