Abstract:
The fuzzy transportation problem constitutes a specialized class of fuzzy linear programming problems (LPPs), which is designed to minimize total fuzzy transportation cost, and satisfy the constraints of both supply and demand. The fuzzy optimization models incorporate fuzzy constraints and objectives, enabling decision-makers to make more robust and flexible transportation plans. As a fundamental optimization model in logistics and operations research, it seeks an optimal distribution strategy that ensures all supply sources as well as demands meet requirements at the lowest possible cost through finding an initial basic feasible solution (IBFS). This paper puts forward a new transportation method called (MSVAM). The unique contribution of the new proposed method lies in minimizing the total transportation cost compared to other existing methods, while reducing the time and effort of the computational process. To validate the effectiveness and applicability of the proposed method, a number of examples (one trapezoidal and the other hexagonal) are solved using MSVAM, and compared with other contemporary methods.
Keywords: Transportation Problem, FTP, IBFS, VAM, SVAM, Robust Ranking Method, MSVAM
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