7511
2019
eng
2:1
2:18
75
conferenceobject
Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
Dagstuhl, Germany
0
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New Perspectives on PESP: T-Partitions and Separators
In the planning process of public transportation companies, designing the timetable is among the core planning steps. In particular in the case of periodic (or cyclic) services, the Periodic Event Scheduling Problem (PESP) is well-established to compute high-quality periodic timetables.
We are considering algorithms for computing good solutions for the very basic PESP with no additional extra features as add-ons. The first of these algorithms generalizes several primal heuristics that had been proposed in the past, such as single-node cuts and the modulo network simplex algorithm. We consider partitions of the graph, and identify so-called delay cuts as a structure that allows to generalize several previous heuristics. In particular, when no more improving delay cut can be found, we already know that the other heuristics could not improve either.
The second of these algorithms turns a strategy, that had been discussed in the past, upside-down: Instead of gluing together the network line-by-line in a bottom-up way, we develop a divide-and-conquer-like top-down approach to separate the initial problem into two easier subproblems such that the information loss along their cutset edges is as small as possible.
We are aware that there may be PESP instances that do not fit well the separator setting. Yet, on the RxLy-instances of PESPlib in our experimental computations, we come up with good primal solutions and dual bounds. In particular, on the largest instance (R4L4), this new separator approach, which applies a state-of-the-art solver as subroutine, is able to come up with better dual bounds than purely applying this state-of-the-art solver in the very same time.
19th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2019)
10.4230/OASIcs.ATMOS.2019.2
OpenAccess Series in Informatics (OASIcs)
yes
urn:nbn:de:0297-zib-73853
false
true
Niels Lindner
Niels Lindner
Valentina Cacchiani
Christian Liebchen
Alberto Marchetti-Spaccamela
Mathematical Optimization
Lindner, Niels
ECMath-MI7