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Exploring the Potential of GPU Computing in Train Rescheduling
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
2019 (English)In: Proceedings of the 8th International Conference on Railway Operations Modelling and Analysis, Norrköping, 2019., 2019Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
2019.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-18510OAI: oai:DiVA.org:bth-18510DiVA, id: diva2:1340179
Conference
8th International Conference on Railway Operations Modelling and Analysis
Available from: 2019-08-02 Created: 2019-08-02 Last updated: 2019-08-15Bibliographically approved
In thesis
1. Parallel algorithms for real-time railway rescheduling
Open this publication in new window or tab >>Parallel algorithms for real-time railway rescheduling
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In railway traffic systems, it is essential to achieve a high punctuality to satisfy the goals of the involved stakeholders. Thus, whenever disturbances occur, it is important to effectively reschedule trains while considering the perspectives of various stakeholders. The train rescheduling problem is a complex task to solve, both from a practical and a computational perspective. From the latter perspective, a reason for the complexity is that the rescheduling solution(s) of interest may be dispersed across a large solution space. This space needs to be navigated fast while avoiding portions leading to undesirable solutions and exploring portions leading to potentially desirable solutions. The use of parallel computing enables such a fast navigation of the search tree. Though competitive algorithmic approaches for train rescheduling are a widespread topic of research, limited research has been conducted to explore the opportunities and challenges in parallelizing them.

This thesis presents research studies on how trains can be effectively rescheduled while considering the perspectives of passengers along with that of other stakeholders. Parallel computing is employed, with the aim of advancing knowledge about parallel algorithms for solving the problem under consideration.

The presented research contributes with parallel algorithms that reschedule a train timetable during disturbances and studies the incorporation of passenger perspectives during rescheduling. Results show that the use of parallel algorithms for train rescheduling improves the speed of solution space navigation and the quality of the obtained solution(s) within the computational time limit.

This thesis consists of an introduction and overview of the work, followed by four research papers which present: (1) A literature review of studies that propose and apply computational support for train rescheduling with a passenger-oriented objective; (2) A parallel heuristic algorithm to solve the train rescheduling problem on a multi-core parallel architecture; (3) A conflict detection module for train rescheduling, which performs its computations on a graphics processing unit; and (4) A redesigned parallel algorithm that considers multiple objectives while rescheduling.

Place, publisher, year, edition, pages
Sweden: Blekinge Institute of Technology, 2019. p. 184
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 9
National Category
Computer Sciences
Identifiers
urn:nbn:se:bth-18511 (URN)978-91-7295-378-9 (ISBN)
Presentation
2019-10-17, J1640, Campus Gräsvik, Karlskrona, 09:00 (English)
Opponent
Supervisors
Available from: 2019-08-02 Created: 2019-08-02 Last updated: 2019-09-17Bibliographically approved

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Josyula, Sai PrashanthTörnquist Krasemann, JohannaLundberg, Lars

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CiteExportLink to record
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Citation style
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