Non-discriminatory train dispatching in a rail transport market with multiple competing and collaborative train operating companies |
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| Institution: | 1. Section Transport Engineering and Logistics, Department of Maritime and Transport Technology, Faculty of Mechanical, Maritime 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. University of Westminster, 35 Marylebone Road, London NW1 5LS, United Kingdom;2. Castelldefels Telecommunications and Aeronautical Engineering School (EETAC), Office C3-104, UPC. Av. Esteve Terradas, 5. Castelldefels 08860, Catalonia, Spain;1. Department of Management Engineering, Technical University of Denmark, Produktionstorvet DTU, Building 424, 2800 Kgs. Lyngby, Denmark;2. KU Leuven Mobility Research Centre - CIB, KU Leuven, Celestijnenlaan 300, Box 2422, 3001 Leuven, Belgium;1. SINTEF ICT, Oslo, Norway;2. Jernbaneverket, Capacity Planning Department, Oslo, Norway;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 |
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| Abstract: | Train dispatching is vital for the punctuality of train services, which is critical for a train operating company (TOC) to maintain its competitiveness. Due to the introduction of competition in the railway transport market, the issue of discrimination is attracting more and more attention. This paper focuses on delivering non-discriminatory train dispatching solutions while multiple TOCs are competing in a rail transport market, and investigating impacting factors of the inequity of train dispatching solutions. A mixed integer linear programming (MILP) model is first proposed, in which the inequity of competitors (i.e., trains and TOCs) is formalized by a set of constraints. In order to provide a more flexible framework, a model is further reformulated where the inequity of competitors is formalized as the maximum individual deviation of competitors’ delay cost from average delay cost in the objective function. Complex infrastructure capacity constraints are considered and modelled through a big M-based approach. The proposed models are solved by a standard MILP solver. A set of comprehensive experiments is conducted on a real-world dataset adapted from the Dutch railway network to test the efficiency, effectiveness, and applicability of the proposed models, as well as determine the trade-off between train delays and delay equity. |
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| Keywords: | Train dispatching Equity Train Operating Company (TOC) Mixed-integer linear programming |
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