The aim of the decision-makers in the transportation industry is to maximize profit by minimizing the transportation cost. The transportation structure is the center of economic activity in the business logistics system. However, transportation costs may vary owing to various unpredictable factors. In this study, cost of the transporting unit is considered as an interval-valued trapezoidal intuitionistic fuzzy number to deal with these uncertainties. The transportation problem with interval-valued trapezoidal intuitionistic fuzzy cost is discussed here, and the costs are ordered by score and score expected functions. As a special case, the interval-valued trapezoidal intuitionistic cost is not converted into crisp numbers to solve the transportation problem and derive the initial basic feasible (IBF) solution through interval-valued intuitionistic costs. Furthermore, the optimality of the derived initial basic feasible solution is checked using the modified distribution (MODI) method. The effectiveness and validation of the developed approach were illustrated using numerical examples.

In dealing with real world transportation problems, several issues are frequently encountered as a result of uncontrollable factors. To deal this uncertainties, many authors have suggested transportation problems with intuitionistic fuzzy parameters. In this article, fully intuitionistic fuzzy transportation problem (InFTP) is considered in which the parameters are triangular intuitionistic fuzzy numbers. To solve this, initially intuitionistic fuzzy branch and bound technique is applied to get the initial basic feasible solution and then intuitionistic fuzzy modified distribution method is applied to acquire the optimal solution of the fully InFTP. Also a new ordering is developed here in which the compensation, linearity and additive property is satisfied. The optimal solution obtained from the proposed method satisfies the condition of optimality and feasibility. Finally two numerical examples are provided to show the effectiveness of the proposed method. From the comparative analysis, the proposed approach shows better optimal solution than existing methods.

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