90C08 Special problems of linear programming (transportation, multi-index, etc.)
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Today the railway timetabling process and the track allocation
is one of the most challenging problems to solve by a railway company.
Especially due to the deregulation of the transport market in the recent years several
suppliers of railway traffic have entered the market in Europe. This leads to more
potential conflicts between trains caused by an increasing demand of train paths.
Planning and operating railway transportation systems is extremely hard due
to the combinatorial complexity of the underlying discrete optimization problems,
the technical intricacies, and the immense size of the problem instances.
In order to make best use of the infrastructure and to ensure economic operation,
efficient planning of the railway operation is indispensable.
Mathematical optimization models and algorithms can help
to automatize and tackle these challenges.
Our contribution in this paper is to present a renewed planning process
due to the liberalization in Europe and an associated concept for track allocation, that consists
of three important parts, simulation, aggregation, and optimization.
Furthermore, we present results of our general framework for real world data.
This survey concerns optimization problems arising in the design of survivable communication networks. It turns out that such problems can be modeled in a natural way as non-compact linear programming formulations based on multicommodity flow network models. These non-compact formulations involve an exponential number of path flow variables, and therefore require column generation to be solved to optimality. We consider several path-based survivability mechanisms and present results, both known and new, on the complexity of the corresponding column generation problems (called the pricing problems). We discuss results for the case of the single link (or node) failures scenarios, and extend the considerations to multiple link failures. Further, we classify the design problems corresponding to different survivability mechanisms according to the structure of their pricing problem. Finally, we show that almost all encountered pricing problems are hard to solve for scenarios admitting multiple failures.
We present formulae for the corner points of the multidimensional Hausdorff and Dale Polytopes and show how these results can be used to improve linear programming models for computing e.\,g.\ moments of exit distribution of diffusion processes. Specifically, we compute the mean exit time of twodimensional Brownian motion from the unit square and the unit triangle, as well as higher moments of the exit time of time space Brownian motion from a triangle.
Anwendungen der Mathematik in der Verkehrs- und Transporttechnologie haben eine große und bedeutende Tradition. Natürlich wurden die ersten Fahrzeuge mit der ingenieurmäßigen Methode von Versuch, Irrtum und Verbesserung entworfen. Aber schon sehr bald kamen mathematische Berechnungen hinzu, mit denen mechanische Eigenschaften von Fahrzeugteilen ermittelt und zum Teil optimiert wurden. Die hierzu erforderliche Mathematik wurde in diesem Jahrhundert zu einem mächtigen Werkzeugkasten ausgebaut. Mit diesem kann man heute z.B. hocheffiziente Motoren mit geringem Schadstoffausstoß entwerfen, aerodynamisch günstige Fahrzeugprofile ermitteln und Flugzeugflügel berechnen, die die gewünschte Last sicher und mit geringem Treibstoffaufwand tragen. Die Mathematik unterstützt die Technologie des Verkehrs beginnend bei globalen Designfragen bis hin zur Spezifizierung von Materialeigenschaften kleinster Bauteile; sie berechnet mit hoher Präzision energieoptimale Bahnen von Raumflugkörpern oder zeitoptimale Trajektorien für Flugzeuge, steuert automatische Roboteranlagen oder innerbetriebliche Transportsysteme.