Multi-objective optimization of train routing problem combined with train scheduling on a high-speed railway network |
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| Institution: | 1. School of Transportation & Logistics, Southwest Jiaotong University, Chengdu, China;2. Process quality and Innovation, Netherlands Railways, Utrecht, The Netherlands;3. Rotterdam School of Management, Erasmus University, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands;4. School of Industrial Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands;1. Section Transport Engineering and Logistics, Department of Maritime and Transport Technology, Faculty of Mechanical, Marine and Materials Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands;2. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, No.3 ShangYuanCun, HaiDian District, Beijing 100044, China;1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China;2. College of Science, Nanchang Institute of Technology, Jiangxi 330099, China;1. Transport and Mobility Laboratory (TRANSP-OR), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland;2. Delft University of Technology, Faculty of Technology, Policy and Management, Transport and Logistics Group, Jaffalaan 5, 2628 BX Delft, Netherlands |
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| Abstract: | Based on train scheduling, this paper puts forward a multi-objective optimization model for train routing on high-speed railway network, which can offer an important reference for train plan to provide a better service. The model does not only consider the average travel time of trains, but also take the energy consumption and the user satisfaction into account. Based on this model, an improved GA is designed to solve the train routing problem. The simulation results demonstrate that the accurate algorithm is suitable for a small-scale network, while the improved genetic algorithm based on train control (GATC) applies to a large-scale network. Finally, a sensitivity analysis of the parameters is performed to obtain the ideal parameters; a perturbation analysis shows that the proposed method can quickly handle the train disturbance. |
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| Keywords: | Train routing problem Train scheduling problem Multi-objective optimization model Genetic algorithm |
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