Mitigating oil deficiency during the Strait of Hormuz conflict through interval-valued intuitionistic fuzzy credibility numbers with Dombi aggregation, WASPAS, and TOPSIS

Although intuitionistic fuzzy sets, Pythagorean fuzzy sets, bipolar fuzzy sets, etc., prove very important when we are dealing with problems regarding uncertainty, having many applications in different fields of real life, they primarily utilize only non-membership and membership values for information, and mostly they provide us with effective and reliable results. However, when we incorporate interval-valued values into these models, highly robust and more accurate results can be achieved. By this, the quality of the solution can be enhanced. In this paper, we propose an interval-valued intuitionistic fuzzy (IVIF) credibility number (IVIFCN) set so that we can get accurate information in cases in which decision making (DM) is needed in an emergency by the assistance of interval-valued non-membership and membership grades with their credibilities. Freedom is granted to DM makers to examine alternatives and multiple objects in the world, and a model is developed containing uncertainty and hesitancy in experimental data related to the global oil shortage. The Dombi aggregation operator, WASPAS, and TOPSIS are used to incorporate the interval-valued estimations, while different procedures are used to find the best way to overcome this huge shortage of oil globally. In addition, a numerical analysis regarding the oil crisis serves as an application of emergency DM and is based on the developed IVIFCN Dombi weighted averaging operator (IVIFCNDWAO). The basic purpose of mathematical illustration is to expose the reasoning as well as the abilities of depicted aggregation operators (AOs).