  Using strategic timetables as input for railway network design has become
increasingly popular among western European railway infrastructure operators.
Although both railway timetabling and railway network design on their own are
well covered by academic research, there is still a gap in the literature
concerning timetable-based network design. Therefore, we propose a
mixed-integer linear program to design railway infrastructure so that the
demand derived from a strategic timetable can be satisfied with minimal
infrastructure costs. The demand is given by a list of trains, each featuring
start and destination nodes as well as time bounds and a set of frequency and
transfer constraints that capture the strategic timetable's main
characteristics. During the optimization, the solver decides which railway
lines need to be built or expanded and whether travel or headway times must be
shortened to meet the demand. Since strategic timetables are subject to
uncertainty, we expand the optimization model to a robust version. Uncertain
timetables are modelled as discrete scenarios, while uncertain freight train
demand is modelled using optional trains, which can be inserted into the
resulting timetable if they do not require additional infrastructure. We
present computational results for both the deterministic and the robust case
and give an outlook on further research.
