A Multi-Operator Framework of Triangular Interval Type-2 Fuzzy Prioritized Aggregation in Expert Evaluation

When many people and many factors are difficult due to uncertainty and ambiguous information, to make decisions in real situations. To address this, Fuzzy sets are used, of which interval type-2 fuzzy sets are particularly good at dealing with larger levels of uncertainty. In this paper, we set up a new concept called triangular interval type-2 fuzzy set. This is simple to work with and is still effective in presenting uncertainty. The main goal of this work is to develop new opportunities for combing information from different people using prioritized fuzzy aggregation operators. These include average, geometric and harmonic operators and they allow us to give importance not just to the criteria but also to the people making the decisions. It defines how these operators work, examine their properties and demonstrates how to apply them when making actual decisions. To prove the usefulness of our method. We apply it to a real-world example related to selecting the right decision in multi-criteria decision-making process. We also compare existing methods and show that these are better in terms of handling uncertainty and achieve more reliable results. In the future, this work can be extended to use fuzzy statements of the intuitionistic type and use them to apply a changing environment. On large scale, we can use these operators to make feasible decision with different priorities of experts and criteria in uncertain conditions.