@misc{BorndoerferEulerKarbsteinetal.2018, author = {Bornd{\"o}rfer, Ralf and Euler, Ricardo and Karbstein, Marika and Mett, Fabian}, title = {Ein mathematisches Modell zur Beschreibung von Preissystemen im {\"o}V}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-70564}, year = {2018}, abstract = {Dieses Dokument fasst den Stand der mathematischen Modellierung von Preissystemen des {\"o}V mittels eines am ZIB entwickelten Tarifgraphenmodells zusammen. Damit sind sehr einfache und konzise Beschreibungen von Tarifstrukturen m{\"o}glich, die sich algorithmisch behandeln lassen: Durch das zeitgleiche Tracken eines Pfades im Routinggraphen im Tarifgraphen kann schon w{\"a}hrend einer Routenberechnung der Preis bestimmt werden. Wir beschreiben zun{\"a}chst das Konzept. Die konkrete Realisierung wird im Folgenden beispielhaft an den Tarifsystemen der Verkehrsverb{\"u}nde Warnow, MDV, Vogtland, Bremen/Niedersachsen, Berlin/Brandenburg und Mittelsachsen erl{\"a}utert. Anschließend folgen {\"U}berlegungen zur konkreten Implementierung von Kurzstrecken-Tarifen und zur Behandlung des Verbund{\"u}bergriffs.}, language = {de} } @misc{EulerBorndoerferStrunketal.2021, author = {Euler, Ricardo and Bornd{\"o}rfer, Ralf and Strunk, Timo and Takkula, Tuomo}, title = {ULD Build-Up Scheduling with Dynamic Batching in an Air Freight Hub}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-83482}, year = {2021}, abstract = {Air freight is usually shipped in standardized unit load devices (ULDs). The planning process for the consolidation of transit cargo from inbound flights or locally emerging shipments into ULDs for outbound flights is called build-up scheduling. More specifically, outbound ULDs must be assigned a time and a workstation subject to both workstation capacity constraints and the availability of shipments which in turn depends on break-down decisions for incoming ULDs. ULDs scheduled for the same outbound flight should be built up in temporal and spatial proximity. This serves both to minimize overhead in transportation times and to allow workers to move freight between ULDs. We propose to address this requirement by processing ULDs for the same outbound flight in batches. For the above build-up scheduling problem, we introduce a multi-commodity network design model. Outbound flights are modeled as commodities; transit cargo is represented by cargo flow volume and unpack and batch decisions are represented as design variables. The model is solved with standard MIP solvers on a set of benchmark data. For instances with a limited number of resource conflicts, near-optimal solutions are found in under two hours for a whole week of operations.}, language = {en} } @misc{BrettHobergPachecoetal.2015, author = {Brett, Charles and Hoberg, Rebecca and Pacheco, Meritxell and Smith, Kyle and Bornd{\"o}rfer, Ralf and Euler, Ricardo and Gamrath, Gerwin and Grimm, Boris and Heismann, Olga and Reuther, Markus and Schlechte, Thomas and Tesch, Alexander}, title = {G-RIPS 2014 RailLab - Towards robust rolling stock rotations}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-53475}, year = {2015}, abstract = {The Graduate-Level Research in Industrial Projects (G-RIPS) Program provides an opportunity for high-achieving graduate-level students to work in teams on a real-world research project proposed by a sponsor from industry or the public sector. Each G-RIPS team consists of four international students (two from the US and two from European universities), an academic mentor, and an industrial sponsor. This is the report of the Rail-Lab project on the definition and integration of robustness aspects into optimizing rolling stock schedules. In general, there is a trade-off for complex systems between robustness and efficiency. The ambitious goal was to explore this trade-off by implementing numerical simulations and developing analytic models. In rolling stock planning a very large set of industrial railway requirements, such as vehicle composition, maintenance constraints, infrastructure capacity, and regularity aspects, have to be considered in an integrated model. General hypergraphs provide the modeling power to tackle those requirements. Furthermore, integer programming approaches are able to produce high quality solutions for the deterministic problem. When stochastic time delays are considered, the mathematical programming problem is much more complex and presents additional challenges. Thus, we started with a basic variant of the deterministic case, i.e., we are only considering hypergraphs representing vehicle composition and regularity. We transfered solution approaches for robust optimization from the airline industry to the setting of railways and attained a reasonable measure of robustness. Finally, we present and discuss different methods to optimize this robustness measure.}, language = {en} }