Most of the data in the real world are uncertain and imprecise. One of the methods used for modeling inaccurate concepts is to use fuzzy sets. An extension of fuzzy sets is type-2 fuzzy sets with membership degrees of the type of fuzzy sets. The interval type-2 fuzzy sets are a specific case of type-2 fuzzy sets that are less complex and easier to understand. Several states can be considered based on the position of ambiguity in a fuzzy linear programming problem. In this article, we study the interval type-2 fuzzy linear programming problem with a resource vector that has the imprecision of the vagueness type. These kinds of vagueness are expressed via membership functions. At first, we will review the available methods. Then we present three new methods and finally examine the efficiency of our methods by presenting several examples. Furthermore, the results of our methods will be compared with those of the reviewed methods. Also, we compare our methods with each other.
Mathematics Subject Classification (2020) 90C70