Gaussian type-2 fuzzy cooperative game based on reduction method: An application to multi-drug resistance problem

Many developments of fuzzy sets have been suggested to accomplish uncertain information in real-world problems. But, in the greatest cases, fuzzy sets in two- dimensions or type-1 fuzzy sets are measured. Incomplete information can indeed be complicated to manage as it creates gaps in understanding. Sporadically, the insufficiency of the data depends upon the extent of time or source, or both. In that case, type-1 fuzzy sets are not adequate to describe the situation. A three-dimensional of the fuzzy set, or type-2 fuzzy set, is utilized here to associate this gap. In the present study, we aim to improve cooperative games in Gaussian type-2 fuzzy environments. To do this, we first delineate the mean reduction and critical value method in Gaussian type-2 fuzzy environments and their properties. A composite strategy combining parametric programming and fuzzy programming is proposed to resolve the created bi-level programming problem in the course of the cooperative game. The proposed methodology is outlined with the multiple drug resistance implementation problem to verify the applicability and validity.