A node importance evaluation method integrating static and dynamic indicators with management decision requirements

Focusing on the needs of road network node importance evaluation and the limitations of existing methods, a novel method to comprehensively evaluate road network node importance considering the influence of operating state changes is proposed. First, an evaluation index system combining static and dynamic indexes is constructed. Therefore, an impact evaluation model of the topological potential is proposed to reflect the operating state of the road network. Second, the integrated weighting method based on multi-objective programming is proposed to determine the final weight of the evaluation index and the sorting result of node importance; further, the particle swarm optimization algorithm is employed to solve this problem. Third, a node grading algorithm based on various sorting results is proposed. Finally, an experimental scheme is designed which verifies the rationality of our proposed methods, algorithms, and theories based on a case study in Xining City. A change in the evaluation index influences the importance of nodes and their sorting, and the dynamic index of the change in road network operation state should be considered. The change in the index weight significantly influences the evaluation of node importance and its sorting and the weight of the index should be reasonably determined; important nodes are more reliable when graded according to the internal relationship and rules of various sorting results. Our proposed method can determine the index weight, node importance sorting, and evaluate the importance of nodes in road networks.