Research on optimization of subway operating schedule based on case database

Abstract

Aiming at the optimization problem of subway operating schedule, this paper integrates the case retrieval method, so that enterprises can quickly find the best operating schedule corresponding to the situation. Taking Nanjing Metro as the case background, this paper analyzes the factors affecting subway operation energy consumption, uses AHP method and Entropy method to calculate subjective and objective weights, and puts forward the AHP-Entropy weighting method based on linear combination to solve the problem of large deviation between subjective and objective weights and combined weights. Then the variable weight nearest neighbor method is used to calculate the similarity of cases, and the applicable cases are obtained, and the optimal operation schedule is selected according to the operation energy consumption. Finally, the validity of the case retrieval method proposed in this paper is verified, and the results show that the linear combination-based AHP-Entropy weighting method combined with the variable weight nearest neighbor method has better stability.