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Development of hybrid optimization of train schedules model for N-track rail corridors
Institution:1. Departamento de Organización Industrial y Gestión de Empresas I (Industrial Engineering and Management Science), Universidad de Sevilla, Spain;2. Departamento de Matemáticas del Área Industrial, E.T.S. Ingenieros Industriales, Universidad Politécnica de Madrid, Spain;3. Instituto Carlos I, Universidad de Granada, Spain;1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China;2. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China;3. Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA;4. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
Abstract:From a capacity perspective, efficient utilization of a railway corridor has two main objectives; avoidance of schedule conflicts, and finding a proper balance between capacity utilization and level of service (LOS). There are several timetable tools and commercial rail simulation packages available to assist in reaching these objectives, but few of them offer both automatic train conflict resolution and automatic timetable management features for the different types of corridor configurations. This research presents a new rescheduling model to address some of the current limitations. The multi-objective linear programming (LP) model is called “Hybrid Optimization of Train Schedules” (HOTS), and it works together with commercial rail simulation tools to improve capacity utilization or LOS metrics. The HOTS model uses both conflict resolution and timetable compression techniques and is applicable to single-, double-, and multiple-track corridors (N-track networks), using both directional and bi-directional operations. This paper presents the approach, formulation and data requirements for the HOTS model. Single and multi-track case studies test and demonstrate the model’s train conflict resolution and timetable compression capabilities, and the model’s results are validated by using RailSys simulation package. The HOTS model performs well in each tested scenario, providing comparable results (either improved or similar) to the commercial packages.
Keywords:Railway optimization  Train scheduling  Hybrid optimization  Railway capacity  Timetable compression technique
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