Yiwen Quan. Research on BP Neural Network Supplier Evaluation Model Based on Genetic Algorithm. Dynamic Systems and Applications 29 (2020) No. 4, 1417 – 1431

https://doi.org/10.46719/dsa202029430

ABSTRACT.
The rapid development of information technology and economic globalization has brought a series of new and severe economic competitive pressures to enterprises. In order to meet the market demand in the modern environment, enterprises must coordinate and integrate resources to enhance the competitiveness of the entire supply chain. Dynamic supply chain performance evaluation is a complex evaluation system that includes multiple indicators of input and output. Each performance indicator has fuzziness, uncertainty, a large number of performance indicators and non-linear correlation between them. Under the mode of supply chain management, the relationship between suppliers and manufacturers is no longer a simple commodity trading relationship, they are a community of interests, through the complementary advantages and coordination effects, they can produce the advantages that enterprises can not produce when they compete alone. Based on the theory of supply chain quality management, this paper constructs a BP neural network supplier evaluation model based on genetic algorithm.

Key words: Information technology; Supplier evaluation; Neural network; Genetic algorithm