Georgia Institute of Technology
Models and algorithms for dynamic real-time freight train re-routing
Abstract
dc:description.abstractThis dissertation focuses on solving a train re-routing problem in a near real-time context for a freight train carrier operating over a large network. A holistic evaluation framework is developed using a time-space network model. Computational results using data from a class I railroad in the United States are used to determine the subset of problem instances that can be solved using the evaluation framework by systematically evaluating all solutions. Solving the remaining problem instances is addressed by developing two solution methodologies that leverage the evaluation framework: an optimization-based approach and a search-based heuristic approach. A further problem variant is also introduced where rail terminal processing rate is a non-constant function of the traffic at the rail terminal. The above approaches are extended to address the problem variant. Computational results are presented for a comprehensive set of problem instances created using data from a class I railroad in the United States. Results indicate the tractability of the optimization-based approach for large-scale instances, practical solution time with reasonable compute resources, as well as the robustness of solution quality to increases in the number of candidate trains. The solution time of the search-based heuristic approach is furthermore shown to be robust to increases in network traffic volume. The results are discussed in detail, along with implications for future research.
Degree
thesis:*- Level thesis:degree_level
- Doctoral
- Department dc:contributor.department
- Industrial and Systems Engineering
- Grantor dc:publisher
- Georgia Institute of Technology
- Year dc:date.issued
- 2018
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Parcham-Kashani, Alborz
- Advisor dc:contributor.advisor
-
- Erera, Alan L.
- Committee members dc:contributor.committeemember
-
- Sokol, Joel
- Vande Vate, John
- Goldsman, David
- Ramcharan, David
Subjects
dc:subject × 6Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1853/60774
- OAI identifier oai:identifier
- oai:repository.gatech.edu:1853/60774