Optimizing Supplier Selection and Resource Allocation Problems in Intelligent Purchasing Systems Based on Decision Tree Algorithms

Reasonable and scientific supplier selection and resource allocation is a prerequisite for enterprises to optimize the quality of supply chain and avoid business risks. In this paper, we select multiple supplier evaluation indexes, use decision tree algorithm to train and calculate the hierarchy of suppliers to determine the supplier options that can be selected. Then the main body of procurement resource planning decision-making is divided into three types: purchaser, database vendor, and customer, to establish a multi-objective model for optimal allocation of procurement resources, and the model is optimized by genetic algorithm to solve the optimal allocation scheme of procurement resources. The supplier selection method based on decision tree can realize the optimal selection of suppliers by constructing a decision tree and transforming it into If-then classification rules. The procurement solutions based on genetic algorithm are 10.44%, 4.31%, and 5.14% higher than B, C, and D solutions, respectively, for better allocation of procurement resources.