Integrated optimization of multi‐vehicle‐type timetabling and scheduling to accommodate periodic passenger flow

Abstract A method was developed for integrating the process of multitype bus timetable generation and chains of trips formed by considering multiperiod passenger flow characteristics. First, the cumulative passenger demand curve was fitted and combined with the vehicle trajectory. Second, according to the results, the combined departure interval for multiple vehicle types was determined, and a one‐way possible timetable set was established. Third, considering the departure time window, the upward and downward possible timetable sets were connected. A bi‐objective mixed integer nonlinear programming model based on a spatiotemporal network was developed through two‐way matching. The objective of the model was to minimize the generalized fleet cost (a problem solved by the continuous deficit function of multiple vehicle types) and passenger waiting time. For two‐way matching, the computational complexity was reduced according to the postroot jump traversal rule, and the 𝑘‐shortest path algorithm was used to solve the bi‐objective Pareto‐optimal solution set. Finally, the Harbin No. 96 bus line was used as an example to validate the proposed model and algorithm. The optimization reduced the bus purchase cost by 51.28%, energy loss cost by 31.78%, and passenger waiting time by 37.07%, indicating that the proposed model can significantly reduce the costs for bus companies and passengers.