An Optimal Expansion Strategy for the German Railway Network Until 2030

Andreas Bärmann ()
Additional contact information
Andreas Bärmann: FAU Erlangen-Nürnberg

A chapter in Operations Research Proceedings 2016, 2018, pp 3-8 from Springer

Abstract: Abstract This article summarizes the findings of my Ph.D. thesis finished in 2015, whose topic are algorithmic approaches for the solution of network design problems. I focus on the results of a joint project with Deutsche Bahn AG on developing an optimal expansion strategy for the German railway network until 2030 to meet future demands. I have modelled this task as a multi-period network design problem and have derived an efficient decomposition approach to solve it. In a case study on real-world data on the German railway network, I demonstrate both the efficiency of by method as well as the high quality of the solutions it computes.

Date: 2018
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-319-55702-1_1

Ordering information: This item can be ordered from
http://www.springer.com/9783319557021

DOI: 10.1007/978-3-319-55702-1_1

Access Statistics for this chapter

More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().