TOPSIS model for urban public transport network optimization based on AHP and entropy

To optimize the urban public transport network, six constraint indexes and their ranges about the urban public transport network optimization on the purpose of minimizing the general cost and maximizing the service level are systematically researched systematically, and the quantitative functions of five optimization indexes are also established according to spatial dimension, time dimension and value dimension. Firstly, the five optimization indexes are taken as the index set, and planning schemes were taken as the domain set to establish the original decision-making matrix which is standardized by [0, 1] linear transformation. Secondly, weights of optimization indexes are determined by AHP and entropy which considered knowledge and experience of experts and information implicated in data, and the weighted standardized decision-making matrix is built up by the way of combing original decision-making matrix with optimization index weights. Thirdly, the distances of planning schemes to the positive and negative ideal solutions are calculated, and the optimization schemes is determined by calculating the close degrees of the planning schemes about the positive ideal solution which is determined by the TOPSIS. The example shows that this model can adjust the public transport network better, and the result was much more reasonable and practical.