An approach to solve interval valued intuitionistic fuzzy transportation problem of Type-2

In the transportation problem, transportation cost depends on several uncontrollable factors such as fluctuation in the fuel price, weather condition, road condition, etc. In most cases, exact information is utilized, but in the real world applications these quantities are imprecise and unconfirmed. Most researchers studied transportation problem with fuzzy and intuitionistic fuzzy parameters. But, both fuzzy and intuitionistic fuzzy parameters utilize fixed membership and non-membership degrees which do not deal properly with the situation of uncertainty and hesitation. Thus, we are faced with another type of ambiguity that cannot be handled by using fuzzy or intuitionistic fuzzy set. In the current work, we have designed a transportation problem in which supplies and demands are crisp numbers and costs are interval valued intuitionistic fuzzy numbers. This type of problem is termed as interval valued intuitionistic fuzzy transportation problem of Type-2. Hence, to deal with ambiguity and uncertainty in transportation problem, an algorithm is developed to find out the optimal solution of interval valued intuitionistic fuzzy transportation problem of Type-2. Finally the proposed algorithm is illustrated with the help of a numerical example and the results are compared with the existing methods.