The Edge Investment Problem: Upgrading Transit Line Segments with Multiple Investing Parties

Authors Rowan Hoogervorst , Evelien van der Hurk , Philine Schiewe , Anita Schöbel , Reena Urban

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Author Details

Rowan Hoogervorst
  • DTU Management, Technical University of Denmark, Kongens Lyngby, Denmark
Evelien van der Hurk
  • DTU Management, Technical University of Denmark, Kongens Lyngby, Denmark
Philine Schiewe
  • Department of Mathematics, Technische Universität Kaiserslautern, Germany
Anita Schöbel
  • Department of Mathematics, Technische Universität Kaiserslautern, Germany
  • Fraunhofer-Institut für Techno- und Wirtschaftsmathematik ITWM, Kaiserslautern, Germany
Reena Urban
  • Department of Mathematics, Technische Universität Kaiserslautern, Germany


We would like to thank the Region H [0205-00005B] and Movia for their efforts to provide insight into the planning process of the BRT system and for the provision of data.

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Rowan Hoogervorst, Evelien van der Hurk, Philine Schiewe, Anita Schöbel, and Reena Urban. The Edge Investment Problem: Upgrading Transit Line Segments with Multiple Investing Parties. In 22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022). Open Access Series in Informatics (OASIcs), Volume 106, pp. 9:1-9:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


Bus Rapid Transit (BRT) systems can provide a fast and reliable service to passengers at lower costs compared to tram, metro and train systems. Therefore, they can be of great value to attract more passengers to use public transport, which is vital in reaching the Paris Agreement Targets. However, the main advantage of BRT systems, namely their flexible implementation, also leads to the risk that the system is only implemented partially to save costs. This paper focuses therefore on the Edge Investment Problem: Which edges (segments) of a bus line should be upgraded to full-level BRT? Motivated by the construction of a new BRT line around Copenhagen, we consider a setting in which multiple parties are responsible for different segments of the line. Each party has a limited budget and can adjust its investments according to the benefits provided to its passengers. We suggest two ways to determine the number of newly attracted passengers, prove that the corresponding problems are NP-hard and identify special cases that can be solved in polynomial time. In addition, problem relaxations are presented that yield dual bounds. Moreover, we perform an extensive numerical comparison in which we evaluate the extent to which these two ways of modeling demand impact the computational performance and the choice of edges to be upgraded.

Subject Classification

ACM Subject Classification
  • Applied computing → Transportation
  • Mathematics of computing → Combinatorial optimization
  • Applied computing → Operations research
  • Network Design
  • Public Transport
  • Bus Rapid Transit
  • Modeling


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