A parallel heuristic for fast train dispatching during railway traffic disturbances: Early results

Document type: Conference Papers
Peer reviewed: Yes
Full text:
Author(s): Syed Muhammad Zeeshan Iqbal, Håkan Grahn, Johanna Törnquist Krasemann
Title: A parallel heuristic for fast train dispatching during railway traffic disturbances: Early results
Conference name: 1st International Conference on Operations Research and Enterprise Systems, ICORES
Year: 2012
Pagination: 405-414
ISBN: 978-989842597-3
City: Vilamoura, Algarve
Organization: Blekinge Institute of Technology
Department: School of Computing (Sektionen för datavetenskap och kommunikation)
School of Computing S-371 79 Karlskrona
+46 455 38 50 00
http://www.bth.se/com
Language: English
Abstract: Railways are an important part of the infrastructure in most countries. As the railway networks become more and more saturated, even small traffic disturbances can propagate and have severe consequences. Therefore, efficient re-scheduling support for the traffic managers is needed. In this paper, the train real-time re-scheduling problem is studied in order to minimize the total delay, subject to a set of safety and operational constraints. We propose a parallel greedy algorithm based on a depth-first branch-and-bound search strategy. A number of comprehensive numerical experiments are conducted to compare the parallel implementation to the sequential implementation of the same algorithm in terms of the quality of the solution and the number of nodes evaluated. The comparison is based on 20 disturbance scenarios from three different types of disturbances. Our results show that the parallel algorithm; (i) efficiently covers a larger portion of the search space by exchanging information about improvements, and (ii) finds better solutions for more complicated disturbances such as infrastructure problems. Our results show that the parallel implementation significantly improves the solution for 5 out of 20 disturbance scenarios, as compared to the sequential algorithm.
Subject: Computer Science\Computersystems
Software Engineering\General
Keywords: Disturbance management; Multiprocessor; Optimization; Parallel computing; Railway traffic; Re-scheduling
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