Interval-Valued Intuitionistic Fuzzy Soft Sets Based Decision-Making and Parameter Reduction

In a typical formulation of decision-making under uncertainty, a decision-maker must choose a single-optimal option among many possible options. However, the problem of selecting a unique and optimal choice has remained a significant challenge to solve. In this article, we propose a new interval-valued intuitionistic fuzzy soft set (IVIFSS) based decision-making approach to address this problem. The proposed approach is based on the choice value and score value of membership/nonmembership degrees. Furthermore, three parameter reduction algorithms are proposed. We apply the proposed approaches on a real application to demonstrate their working and effectiveness. We also compare the proposed approach against the adjustable IVIFSSs approach and show that the proposed approach has lower computation overhead and enable a decision-maker to choose top options to make a proper decision.

Automated summary

In this article, a new decision-making approach based on IVIFSS is proposed to address the challenge of selecting an optimal choice under uncertainty. The approach utilizes the choice value and score value of membership/nonmembership degrees and also includes three parameter reduction algorithms. The effectiveness and computational efficiency of the proposed approach are demonstrated through a comparison with the adjustable IVIFSSs approach and a real application.