New method for solving Fuzzy transportation problems with LR flat fuzzy numbers

Transportation problems have various applications in logistics and supply chains for reducing costs. In real-life situations, the parameters of transportation problems may not be known precisely because of uncontrollable factors. Herein, we propose a new method for solving fuzzy transportation problems (FTPs) in which the transportation costs and supply and demand are represented by non-negative LR flat fuzzy numbers. The FTP is converted into four transportation problems, which are solved using standard transportation simplex algorithms. The advantages of the proposed method over existing methods are discussed in the context of two application examples. The results show that the proposed method is simpler and computationally more efficient than existing methods in the literature.

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