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  • 2020-2023  (1)
  • 2010-2014  (3)
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  • 1
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    Analysis of Micro–Macro Transformations of Railway Networks (2014)
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    Publication Date: 2020-08-05
    Description: A common technique in the solution of large or complex optimization problems is the use of micro–macro transformations. In this paper, we carry out a theoretical analysis of such transformations for the track allocation problem in railway networks. We prove that the cumulative rounding technique of Schlechte et al. satisfies two of three natural optimality criteria and that this performance cannot be improved. We also show that under extreme circumstances, this technique can perform inconveniently by underestimating the global optimal value.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 2
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    Re-Optimization of Rolling Stock Rotations (2014)
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    Publication Date: 2020-08-05
    Description: The Rolling Stock Rotation Problem is to schedule rail vehicles in order to cover timetabled trips by a cost optimal set of vehicle rotations. The problem integrates several facets of railway optimization, such as vehicle composition, maintenance constraints, and regularity aspects. In industrial applications existing vehicle rotations often have to be re-optimized to deal with timetable changes or construction sites. We present an integrated modeling and algorithmic approach to this task as well as computational results for industrial problem instances of DB Fernverkehr AG.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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    OPUS
  • 3
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    A Coarse-To-Fine Approach to the Railway Rolling Stock Rotation Problem (2014)
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    Publication Date: 2020-08-05
    Description: We propose a new coarse-to-fine approach to solve certain linear programs by column generation. The problems that we address contain layers corresponding to different levels of detail, i.e., coarse layers as well as fine layers. These layers are utilized to design efficient pricing rules. In a nutshell, the method shifts the pricing of a fine linear program to a coarse counterpart. In this way, major decisions are taken in the coarse layer, while minor details are tackled within the fine layer. We elucidate our methodology by an application to a complex railway rolling stock rotation problem. We provide comprehensive computational results that demonstrate the benefit of this new technique for the solution of large scale problems.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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    OPUS
  • 4
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    An LP-based heuristic for Inspector Scheduling (2021)
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    Publication Date: 2022-02-07
    Description: We present a heuristic based on linear programming (LP) for the integrated tour and crew roster planning of toll enforcement inspectors. Their task is to enforce the proper paying of a distance-based toll on German motorways. This leads to an integrated tour planning and duty rostering problem; it is called Toll Enforcement Problem (TEP). We tackle the TEP by a standard multi-commodity flow model with some extensions in order to incorporate the control tours. The heuristic consists of two variants. The first, called Price & Branch, is a column generation approach to solve the model’s LP relaxation by pricing tour and roster arc variables. Then, we compute an integer feasible solution by restricting to all variables that were priced. The second is a coarse-to-fine approach. Its basic idea is projecting variables to an aggregated variable space, which is much smaller. The aim is to spend as much algorithmic effort in this coarse model as possible. For both heuristic procedures we will show that feasible solutions of high quality can be computed even for large scale industrial instances.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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    OPUS
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