Chapter
Apr 26, 2012
An Effective Meta-Heuristic Technique for Solving Train Scheduling Problem
Authors: M. B. Khan [email protected], Wangbo Fan, and Dianye ZhangAuthor Affiliations
Publication: International Conference on Transportation Engineering 2007
Abstract
This paper presents a hybrid evolutionary technique for solving train-scheduling problem. The proposed approach exploits key features of genetic algorithm (GA) and Tabu search (TS) in order to find nearly optimal feasible solution. Strategic oscillation is incorporated in GA to diversify the search space. The objective is to minimize the associated delays caused by train conflicts (cross or overtake) that is the waiting times at the train stations. The necessary algorithmic solution is described together with some empirical observations about the performance of our train-scheduling model. The simulation results show that our model is able to produce useful results in terms of minimizing delays and producing nearly optimal schedules.
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© 2007 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
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ASCE Technical Topics:
- Algorithms
- Continuum mechanics
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Hybrid methods
- Infrastructure
- Mathematics
- Methodology (by type)
- Models (by type)
- Motion (dynamics)
- Oscillations
- Railroad stations
- Simulation models
- Solid mechanics
- Terminal facilities
- Transportation engineering
- Transportation management
Authors
Affiliations
College of Traffic and Transportation, Southwest Jiaotong University Chengdu 610031, PR China.E-mail: [email protected]
Wangbo Fan
College of Traffic and Transportation, Southwest Jiaotong University Chengdu 610031, PR China
Dianye Zhang
Professor, Southwest Jiaotong University Chengdu 610031, PR China
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Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.