TY - CHAP A1 - Bortoletto, Enrico A1 - van Lieshout, Rolf Nelson A1 - Masing, Berenike A1 - Lindner, Niels T1 - Periodic Event Scheduling with Flexible Infrastructure Assignment T2 - 24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024) N2 - We present novel extensions of the Periodic Event Scheduling Problem (PESP) that integrate the assignment of activities to infrastructure elements. An application of this is railway timetabling, as station and platform capacities are limited and need to be taken into account. We show that an assignment of activities to platforms can always be made periodic, and that it can be beneficial to allow larger periods for the assignment than for the timetable. We present mixed-integer programming formulations for the general problem, as well as for the practically relevant case when multiple platforms can be considered equivalent, for which we present a bipartite matching approach. We finally test and compare these models on real-world instances. Y1 - 2024 U6 - https://doi.org/10.4230/OASIcs.ATMOS.2024.4 VL - 123 SP - 4:1 EP - 4:18 ER - TY - CHAP A1 - Bortoletto, Enrico A1 - Lindner, Niels ED - Voigt, Guido ED - Fliedner, Malte ED - Haase, Knut ED - Brüggemann, Wolfgang ED - Hoberg, Kai ED - Meissner, Jörn T1 - Scaling and Rounding Periodic Event Scheduling Instances to Different Period Times T2 - Operations Research Proceedings 2023 N2 - The Periodic Event Scheduling Problem (PESP) is a notoriously hard combinatorial optimization problem, essential for the design of periodic timetables in public transportation. The coefficients of the integer variables in the standard mixed integer linear programming formulations of PESP are the period time, e.g., 60 for a horizon of one hour with a resolution of one minute. In many application scenarios, lines with different frequencies have to be scheduled, leading to period times with many divisors. It then seems natural to consider derived instances, where the period time is a divisor of the original one, thereby smaller, and bounds are scaled and rounded accordingly. To this end, we identify two rounding schemes: wide and tight. We then discuss the approximation performance of both strategies, in theory and practice. Y1 - 2025 U6 - https://doi.org/10.1007/978-3-031-58405-3_51 SP - 397 EP - 402 ER -