Considering the node importance of transfer station in the regional public transit network, a regional bus timetable optimization model was developed to improve the public transit attraction by reasonably adjusting the headway of various periods to reduce the passengers waiting time and transfer time. To accomplish the optimization, a three-phase method is constructed in this paper. Firstly, because of the difference in the topological network structure and node function, the contribution of various stations to network transportation and transfer efficiency is unique. Thus, topology network structure indices as node betweenness and node degree such as passenger flow at bus transfer stations are considered to evaluate the importance of nodes. Secondly, the system cost, which is consisted of the waiting time cost of non-transfer passengers, the waiting time cost of transfer passengers, and the costs of schedule deviation, is conducted to evaluate the effect of the optimal method conducted in this paper. To minimize the total system cost, a regional bus timetable optimization model is developed and solved with applying a particle swarm optimization algorithm for the appropriate headway between the objective buses. Finally, this method sequentially traverses the whole nodes for optimization according to their importance in the network. To verify the validity of the model, three bus lines in Beijing were taken as an example. The simulation results show that the total system cost can be decreased by 8.6% with the regional bus timetable optimization model.
 

urban traffic; node importance; regional timetable optimization; particle swarm optimization