Research on Enterprise Raw material ordering and Transportation process based on Multi-objective programming and Machine Learning algorithm

Abstract

This paper analyzes the various production factors that affect the building materials enterprises, including the production cost of the enterprise itself and the degree affected by suppliers and transporters. Then, according to the relevant data, the objective function of minimum production cost is established, and under the premise of ensuring production, a mathematical model is established with the influence degree of each related enterprise as the constraint. In this paper, the model is solved to help enterprises make a reasonable production and management plan. First of all, the random forest algorithm is used as a machine learning method to analyze the characteristics of the given supplier. Then we evaluate the importance of each supplier to the production of the enterprise, and then rank it according to the level of influence, and select the top 20 suppliers. Then three goals are selected based on the multi-objective programming algorithm. First, the cost of production is the lowest, that is, the total cost of purchasing all kinds of materials is the least. Second, the loss is the lowest in the process of material transportation. In this paper, the materials collected are divided into three kinds of ABC, thus it is concluded that increasing the purchase of A material and reducing the purchase of C material. Therefore, a multi-objective programming model is established to solve the ordering and transshipment scheme. Finally, the neural network algorithm is used to evaluate the supplier's supply volume and transshipment loss in the next 24 weeks. The main goal is to maximize the production capacity of the enterprise, without considering the material procurement cost and the purchase demand of An and C materials, but still keep the minimum material transfer loss. In this paper, the weight analysis and multi-objective programming algorithm around the ordering and transportation process based on the principle of production enterprises can effectively provide reliable reference analysis for this process that needs to be optimized.