This work presents a comprehensive solution to the last-train timetable optimization and rescheduling problem in metro networks. Based on the transfer demand as well as the complex transfer connection relationships, we propose both a timetable optimization model and a timetable rescheduling model from the passenger-oriented view to maximize the number of served transfer passengers in normal situations and to minimize the number of failed transfer passengers in delayed situations, respectively. Some linear reformulation is adopted to convert the two non-linear models into integer linear programming models, which can be solved by CPLEX efficiently when dealing with a large-scale and complex problem. Finally, a real-world case study derived from the Shenzhen Metro network is carried out to validate the proposed method, and results show that the proposed method is effective in providing decision support for operation agencies.
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