A fuzzy risk-assessment method using a TOPSIS approach based on interval-valued fuzzy numbers

Abstract

Because of the importance of reducing risks in a high-tech corporation, decision makers need a useful method to help them find the alternative with the lowest risk from a given set. In particular, in an uncertain and complex situation, making a choice becomes more difficult for decision makers. In this article, we analyzed the risks of a particular decision in linguistic terms and based on interval-valued fuzzy numbers (IVFNs). We also extended a similarity measure in the technique for order preference based on similarity to the ideal solution (TOPSIS) approach by measuring the similarity of each alternative to positive and negative ideal IVFNs. Rather than calculating the distance between the alternatives and the positive/negative ideal solution in the TOPSIS method, we used the similarity measure between IVFNs to replace distance in this approach. Even with the same distance between IVFNs, the measure may have different shapes or directions, which may lead to nonintuitive results. In the proposed method, we used a fixed ideal solution that could simplify the calculations of a similarity measure between IVFNs. We also applied the similarity measure between IVFNs to the decision-making process to increase the ability of the process to account for risks in a variable, complex, and uncertain environment.