Mathematical programming for minimizing total travelling time of passengers by partial introduction of rapid trains

Abstract

Smart timetabling optimization is a cost-effective way to improve the quality of railway service. Partial introduction of rapid trains is one of the effective methods for improving passenger service quality. However, it is difficult to concretely perform smart train scheduling. In this paper, we apply mixed integer programming for minimizing the total travelling time of passengers to obtain optimal train scheduling for the combination of all-station and partially introduced rapid trains. This method requires higher computational time to obtain the optimal solution than other meta-heuristic methods; however, the solution guarantees to be an optimal one. We also propose an appropriate method to digitize the OD (Origin Destination)-patterns, i.e., the traffic demand inputs between two stations, which are suitable for the framework of the proposed mixed integer programming method. We apply the method to a case study of a commercial subway and demonstrate the advantages of the proposed train service with the partial introduction of rapid trains.