For enterprises, the ordering and transportation process of raw materials is a key link. Aiming at the problem of ordering and transportation of raw materials in enterprises, this paper establishes Topsis comprehensive evaluation model, entropy weight method, 0-1 integer programming model and so on, and uses Matlab, Lingo, Excel and so on to solve it. First of all, the collected data are classified according to A, B and C. Then four indicators are created and calculated: the cooperation rate between each supplier and the production enterprise, the demand satisfaction level of each supplier to the enterprise, the actual market share of each supplier to the same material, and the actual weekly distribution rate of each supplier. Then the Topsis comprehensive evaluation model is established, and the entropy method is used to modify the model, and the comprehensive weights are 0.0408, 0.0555, 0.4495 and 0.4542 respectively, thus the comprehensive score of each supplier is obtained, and the score is sorted, and the supplier data can be screened. The total supply of each supplier to each raw material within 240 weeks is calculated respectively, and the production capacity ratio of each raw material is obtained. Based on this, the rankings of three types of data accounting for the 50 most important suppliers are calculated. Then, with the minimum number of suppliers in the raw material ordering process as the objective function and the weekly production capacity standard as the constraint, a 0-1 integer programming model is established to get at least the number of suppliers. Then the goal programming is carried out around the lowest raw material procurement cost, and the demand of all kinds of raw materials is taken as the constraint, a linear programming model is established, and the results of the ordering plan for the next 24 weeks are shown in Annex A. Taking the minimum value of transport loss as the objective function, a linear programming model is established to solve the transport volume of all kinds of raw materials, and the transfer scheme is obtained. The linear programming model is modified by the loss capacity, and the dynamic programming model is established to get the optimal scheme.
