A New Technique For Deciding On The Interval Type-2 Fuzzy Transportation Problem Based On Interval Linear Programming Problems

In real world problems, the parameters of the solid transportation (ST) problems (supply, demand and capacity of vehicles) are not always accurate. Therefore, in dealing with these problems due to the existence of uncertainty and ambiguity in the data should use fuzzy optimization. Hence, in the main part of fuzzy optimization, we need to model and solve fuzzy linear programming (FLP) problems that its parameters are interval type-2 fuzzy numbers (IT2FNs). While, the studies on model of interval type-2 FLP problem have been very limited. So, in this article, we consider the parameters of the ST problem as interval type-2 triangular fuzzy numbers (IT2TFNs) and solve it. Then, we proposed a new approach to solve it by extension the notion of the nearest interval proximation. Finally, in special case, we explain and analyze the numerical example of interval type-2 fuzzy ST problem.