Timetable Rescheduling Considering Headway: A Genetic Algorithm Combined with the Benchmark Time Method

Abstract

This study contributes to dealing with disturbances happening on an urban rail transit line. In order to neutralize the negative effect on passengers, the problem is studied from the passenger-oriented perspective, and a timetable rescheduling model is proposed to reduce the waiting time of all passengers by improving the evenness of headway. Then, the benchmark time method is introduced to determine the specific range of each decision variable, which is combined with an efficient genetic algorithm to solve the large-scale problem within limited time. Finally, some numerical experiments based on a real-world case derived from a Beijing Subway line are carried out. Results show that the proposed method is able to improve the evenness of headway obviously and to generate a good enough rescheduled timetable efficiently.