Passenger-demands-oriented train scheduling for an urban rail transit network |
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| Affiliation: | 1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, PR China;2. Delft Center for Systems and Control, Delft University of Technology, 2628 CD Delft, The Netherlands;1. Department of Management Engineering, Technical University of Denmark, Produktionstorvet 424, 2800 Kgs. Lyngby, Denmark;2. Rotterdam School of Management, Erasmus University, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands;3. School of Industrial Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands;4. Process Quality and Innovation, Netherlands Railways, Utrecht, The Netherlands;1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China;2. Department of Civil Engineering, Auburn University, Auburn, AL 36849, USA;3. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China;4. Beijing Transport Institute, Beijing 100073, China;1. School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China;2. School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287, United States;1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, 1201, SiYuan Building, No. 3 ShangYuanCun, HaiDian District, Beijing 100044, China;2. School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287, USA;1. Future Cities Laboratory, Singapore-ETH Centre, Singapore 138602, Singapore;2. Department of Civil & Environmental Engineering, National University of Singapore, Singapore 117576, Singapore;3. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;4. Institute for Transport Planning and Systems (IVT), ETH Zürich, Zürich CH 8093, Switzerland;1. Interuniversity Research Center on Network Enterprise, Logistics and Transportation (CIRRELT), Canada;2. HEC Montréal, 3000 chemin de la Côte-Sainte-Catherine, Montréal H3T 2A7, Canada;3. School of Engineering, University of Seville, Avenida de los Descubrimientos s/n, 41092 Seville, Spain;4. Faculté des sciences de l’administration, Université Laval, 2325 rue de la Terrasse, Québec G1K 7P4, Canada |
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| Abstract: | This paper considers the train scheduling problem for an urban rail transit network. We propose an event-driven model that involves three types of events, i.e., departure events, arrival events, and passenger arrival rates change events. The routing of the arriving passengers at transfer stations is also included in the train scheduling model. Moreover, the passenger transfer behavior (i.e., walking times and transfer times of passengers) is also taken into account in the model formulation. The resulting optimization problem is a real-valued nonlinear nonconvex problem. Nonlinear programming approaches (e.g., sequential quadratic programming) and evolutionary algorithms (e.g., genetic algorithms) can be used to solve this train scheduling problem. The effectiveness of the event-driven model is evaluated through a case study. |
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| Keywords: | Train scheduling Passenger demands Event-driven Urban rail transit network |
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