This paper ranks and selects suppliers based on their importance while providing the most economical ordering solution and the least lossy forwarding solution under meeting the enterprise capacity requirements. In this paper, four indicators are selected to measure the supplier's supply characteristics, and the entropy weight method is used to determine the weight of each indicator. The evaluation model is constructed using the TOPSIS algorithm to determine the importance of the supplier by

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... ulating the distance from the sample to the ideal solution and the negative ideal solution. Then this paper uses 0-1 planning to establish a linear objective function with whether to choose one supplier as the decision variable and solves with a genetic algorithm to derive the need for at least 162 suppliers. Finally, the most economical ordering solution planning model is established, and the cost function is built and solved to find the ordering solution at its minimum value. Based on the most economical ordering solution, the least loss transshipment solution is developed, and the least loss transshipment solution planning model is developed to obtain the total loss function of raw materials and solve for the minimum value of the transshipment solution with the decision variable of whether to choose this transshipment provider. The final ordering solution obtained using the model in this paper saved approximately 9.1% of production costs, and the designed transportation solution reduced losses by 4.5%.