Research on the Multi-objective Transfer Coordination Optimization of Urban Rail Transit Trains

Abstract

The transfer coordination optimization of trains is an important strategy to improve the service level of urban rail transit. Through analysing the passenger transferring behavior and train movements, a multiobjective optimization model for transfer coordinating urban rail transit trains is established to minimize the total transfer waiting time, train operating cost and fluctuating of departure interval. Furthermore, a genetic algorithm based on a niche selection operator is put forward to find the Pareto set which can provide multiple options for operating managers and the information entropy is used to make a decision for satisfied scheme. At last, a transfer station between Lines No. 2 and No. 5 of the Beijing subway is chosen for optimization the train’s transfer coordination and the results illustrate the effectiveness of the optimization model and algorithm.