Optimization of Rail Transit Network Based on Weighted PCA-TOPSIS Model

The evaluation index system of urban rail transit network, including three levels and five subsystems, is improved based on referencing the research of Chinese cities. The paper proposes the weighted PCA-TOPSIS model to solve the limitation of existing evaluation methods. The method considers the index attribute to build a first matrix, with standardized processing of linear calibration conversion. And building a weighted decision matrix with the subjective G1 method and objective entropy method, which analyzes the preference of decision makers and information of data. The model makes data uncorrelated with dimension reduction of principal component analysis (PCA) and improves the efficiency of multiple-attribute decision-making TOPSIS to choose the optimal scheme. The method is applied to assess Yinchuan rail transit network planning, and the optimal scheme is chosen from the four networks. The result shows that this method is reasonable and effective.