A novel approach to three-way decision model under fuzzy soft dominance degree relations and emergency situation

In this study, we attempt to present a three-way multi criteria decision-making (MCDM) technique with fuzzy soft dominance degree relation based on additive consistency to simultaneously choose the best alternative, rank alternatives, and classify alternatives, which would aid decision-makers in making better decisions. First, we provide the additive consistency based fuzzy soft dominance degree relation. Then, based on the fuzzy soft dominance degree relation, we build the idea of the 0-similarity class and define new relative loss functions with unknown risk coefficient vectors and unknown weights of the alternatives. Further, using 0 similarity classes based conditional probability, we offer a theoretical approach for finding total decision cost to attain the best cost-sensitive granularity selection. Furthermore, we also discuss in detail about the newly proposed three-way MCDM method's decision making mechanisms. We further check the method's viability using the emergency plan selection problem. Comparative assessments demonstrate that the proposed approach has a better decision-making function than several other methods available in the literature. Experimental evaluations demonstrate that the proposed technique consistently rank the considered object and chooses the best one. Furthermore, the suggested technique can satisfy the decision-makers' preferences in the classification choice in addition to offering suitable ranking decision recommendation for decision-makers.