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A parallel algorithm for multi-objective train rescheduling
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
(Engelska)Manuskript (preprint) (Övrigt vetenskapligt)
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:bth-18542OAI: oai:DiVA.org:bth-18542DiVA, id: diva2:1343091
Tillgänglig från: 2019-08-15 Skapad: 2019-08-15 Senast uppdaterad: 2019-09-06Bibliografiskt granskad
Ingår i avhandling
1. Parallel algorithms for real-time railway rescheduling
Öppna denna publikation i ny flik eller fönster >>Parallel algorithms for real-time railway rescheduling
2019 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Sweden: Blekinge Institute of Technology, 2019. s. 184
Serie
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 9
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:bth-18511 (URN)978-91-7295-378-9 (ISBN)
Presentation
2019-10-17, J1640, Campus Gräsvik, Karlskrona, 09:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2019-08-02 Skapad: 2019-08-02 Senast uppdaterad: 2019-09-17Bibliografiskt granskad

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Josyula, Sai PrashanthTörnquist Krasemann, JohannaLundberg, Lars
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Datavetenskap (datalogi)

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