Abstract: Transportation problems have wide applications in logistics and supply chain for reducing the cost. Effective algorithms have been proposed to solve the transportation problem in the case when all of the parameters, namely the supply, demand values and the unit transportation costs, are given in a precise way. However, in real applications, there are many diverse situations due to uncertainty. So, it is significant to investigate the transportation problem under uncertain environment. In this paper, a two-step method is proposed for solving fuzzy transportation problem (FTP) where all of the parameters are represented by non-negative triangular fuzzy numbers. The first is to employ fuzzy arithmetic to convert FTP into a linear programming with fuzzy costs and crisp constraints. The second is to use a new decomposition technique to transform the resulting problem into three crisp bounded transportation problems. The advantages of the proposed method over the existing methods are discussed by an application example. The obtained results show that the method proposed in this study is simpler and computationally more efficient than some existing methods commonly used in the literature.
