Abstract: To address the limitations of single-metric approaches and subjective weighting in most traditional methods for identifying critical nodes in complex networks, a novel critical node identification method based on a VIKOR-GRA model(VIKOR-GRA-Key node identification, VGKNI)was proposed. The entropy weight method and grey relational analysis were employed. Building upon the selection of traditional centrality metrics, the bridge centrality metric was introduced. The proposed algorithm was validated using multiple real-world network datasets and was compared with various other methods through comparative analysis. It was demonstrated by the results that the ranking of critical nodes obtained by the proposed method was reasonable, and that superior monotonicity and simulation recovery effects were shown compared to some traditional methods. Therefore, advantages in handling the problem of identifying critical nodes in complex networks were offered by the method presented in this paper, and a new perspective and approach for complex network research were provided.

Key words: complex networks, key node identification, entropy weighting method, VIKOR-GRA model, bridge centrality