The DOI matches its Crossref record.
A Column Generation Approach to the Urban Transit Crew Scheduling Problem
Abstract
The urban transit crew scheduling problem arises in mass transit organizations which have to create minimal cost bus driver schedules respecting both the collective agreement with labor unions and the bus schedule. We propose a column generation approach to solve the transit crew scheduling problem. The column generation approach decomposes the problem into two parts. The set covering problem chooses a schedule from already known feasible workdays. The second subproblem is a shortest path problem with resource constraints and is used to propose new feasible workdays to improve the current solution of the set covering problem. The approach has been successfully tested on real-life problems.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Branch-and-price: column generation for solving huge integer programs
Barnhart, C., Johnson, E. L., Nemhauser, G. L., Savelsbergh, M. W. P., & Vance, P. H. (1998) · Operations Research · doi:10.1287/opre.46.3.316 · Cited by 2,219
Public transport for smart cities: Recent innovations and future challenges
Kuo, Y.-H., Leung, J. M. Y., & Yan, Y. (2023) · European Journal of Operational Research · doi:10.1016/j.ejor.2022.06.057 · Cited by 201
A survey of resource constrained shortest path problems: Exact solution approaches
Pugliese, L. D. P., & Guerriero, F. (2013) · Networks · doi:10.1002/net.21511 · Cited by 147
A technical review of column generation in integer programming
Wilhelm, W. E. (2001) · Optimization and Engineering · doi:10.1023/a:1013141227104 · Cited by 108
Metadata
- Authors
- Desrochers, M., & Soumis, F.
- Venue
- Transportation Science
- Published
- 1989-02
- Volume
- 23
- Issue
- 1
- Pages
- 1-13
- ISSN
- 0041-1655 (ISSN-L)
- 1526-5447
- OpenAlex
- W2003066927
- Cited by
- 332
- References
- 0
- FWCI
- 4.16
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Column Generation Approach to the Urban Transit Crew Scheduling Problem. https://app.cochat.ai/papers/10.1287/trsc.23.1.1
- The paper
- Desrochers, M., & Soumis, F. (1989). A Column Generation Approach to the Urban Transit Crew Scheduling Problem. Transportation Science. https://doi.org/10.1287/trsc.23.1.1
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.