Heuristic techniques for train scheduling
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Description
Optimising a train schedule on a single line track is known to be NP-Hard with respect to the number of conflicts in the schedule. This makes it difficult to determine optimum solutions to real life problems in reasonable time and raises the need for good heuristic techniques. The heuristics applied and compared in this paper are a local search heuristic with an improved neighbourhood structure, genetic algorithms, tabu search and two hybrid algorithms. When no time constraints are enforced on solution time, the genetic and hybrid algorithms were within five percent of the optimal solution for at least ninety percent of the test problems.
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| ID Code: | 3794 | ||
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| Item Type: | Contribution to Journal (Journal Article) | ||
| Refereed: | Yes | ||
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| Keywords: | Train Scheduling, Local Search, Tabu Search, Genetic Algorithm, Hybrid Algorithm | ||
| DOI: | 10.1023/A:1009672832658 | ||
| ISSN: | 1572-9397 | ||
| Pure ID: | 60078222 | ||
| Divisions: | Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering Current > Research Centres > Australian Research Centre for Aerospace Automation |
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| Copyright Owner: | Copyright 1997 Springer | ||
| Copyright Statement: | The original publication is available at SpringerLink http://www.springerlink.com | ||
| Deposited On: | 31 Mar 2006 00:00 | ||
| Last Modified: | 29 May 2024 14:25 |
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