Benders Decomposition-Based Optimization of Train Departure Frequencies in Metro Networks
A. Daman (Student TU Delft)
Xiaoyu Liu (TU Delft - Team Bart De Schutter)
A. Dabiri (TU Delft - Team Azita Dabiri)
BHK De Schutter (TU Delft - Delft Center for Systems and Control)
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Abstract
Timetables determine the service quality for passengers and the energy
consumption of trains in metro systems. In metro networks, a timetable
can be made by designing train departure frequencies for different
periods of the day, which is typically formulated as a mixed-integer
linear programming (MILP) problem. In this paper, we first apply Benders
decomposition to optimize the departure frequencies considering
time-varying passenger origin-destination demands in metro networks. An
ϵ
-optimal Benders decomposition approach is subsequently used to reduce
the solution time further. The performance of both methods is
illustrated in a simulation-based case study using a grid metro network.
The results show that both the classical Benders decomposition approach
and the
ϵ
-optimal Benders decomposition approach can significantly reduce the
computation time for the optimization of train departure frequencies in
metro networks. In addition, the
ϵ
-optimal Benders decomposition approach can further reduce the solution
time compared to the classical Benders decomposition approach when the
problem scale increases while maintaining an acceptable level of
performance.