Data security decision under interval-valued intuitionistic fuzzy environment with new score function and combined weight

The score function and weight have great influence on the decision result of interval valued intuitionistic fuzzy (IVIF) environment. Historically, decision-making methods have encountered unsatisfactory and even counter-intuitive outcomes when dealing with extreme data. Therefore, in this paper, a new decision-making method based on the interval-valued intuitionistic fuzzy environment is proposed in this paper to address this issue. Firstly, a new score function for interval-valued intuitionistic fuzzy numbers (IVIFNs) is introduced. This function takes into consideration the membership degree, non-membership degree, and data dispersion degree, while also including a pessimism coefficient that can be adjusted by both conservative and radical decision-makers. Secondly, a hybrid method for obtaining objective weights for decision-making criteria is proposed, and the objective weights are integrated with subjective weights. Finally, the effectiveness of the proposed method in dealing with extreme data and providing reasonable sorting of schemes is demonstrated through a case study of data security decision-making. A comparative analysis is also provided. The results demonstrate that the proposed method has both strong theoretical and practical significance.