The Optimization Model and Algorithm for Train Connection at Transfer Stations in Urban Rail Transit Network

In urban rail transit network, the passenger transfer time depends on the train connection states in transfer stations, so the optimization of the connection relations of arrival and departure time among trains is significant to improve the level of transfer service. Here, with the psychology of waiting passengers taken into consideration, the cost function of transfer waiting times has been established. On this basis, an optimization model for train connections at transfer stations was constructed, and a genetic algorithm was designed to solve this model. A computer program implementing this genetic algorithm was written in Microsoft VB.NET. And the program is used to optimize the train operation plans of a simple network which consists of four urban rail lines in Beijing. The results show that the proposed method can effectively reduce the total waiting time cost of all transfer passengers in the network.