Planning problems in passenger railway range from long term strategic decision making to
the detailed planning of operations. Operations research methods have played an …

While methods for optimization under uncertainty have been studied intensely over the past
decades, the explicit consideration of the interplay between uncertainty and time has gained …

We present a new concept for optimization under uncertainty: recoverable robustness. A
solution is recovery robust if it can be recovered by limited means in all likely scenarios …

Robust optimization is a young and emerging field of research having received a
considerable increase of interest over the last decade. In this paper, we argue that the …

This paper provides an overview of railway timetable design in practice and the
combinatorial optimization models that have been proposed for this application, putting …

Robust optimization is an emerging area in research that allows addressing different
optimization problems and specifically industrial optimization problems where there is a …

In this paper we describe a two-stage optimization model for determining robust rolling stock
circulations for passenger trains. Here robustness means that the rolling stock circulations …

In practical optimization problems, disturbances to a given instance are unavoidable due to
unpredictable events which can occur when the system is running. In order to face these …

Finding robust solutions of an optimization problem is an important issue in practice. Various
concepts on how to define the robustness of an algorithm or of a solution have been …

Shunting for Dummies: An Introductory Algorithmic Survey Page 1 Shunting for Dummies:
An Introductory Algorithmic Survey * Michael Gatto, Jens Maue, Matúš Mihalák, and Peter …