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  • 1.
    Högdahl, Johan
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.
    A Simulation-Optimization Approach for Improved Robustness of Railway Timetables2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The timetable is an essential part for the operations of railway traffic, and its quality is considered to have large impact on capacity utilization and reliability of the transport mode. The process of generating a timetable is most often a manual task with limited computer aid, and is known to be a complex planning problem due to inter-train dependencies.

    These inter-train dependencies makes it hard to manually generate feasible timetables, and also makes it hard to improve a given timetable as new conflicts and surprising effects easily can occur.

    As the demand for railway traffic is expected to continue grow, higher frequencies and more saturated timetables are required. However, in many European countries there is also an on-going public debate on the punctuality of the railway, which may worsen by increased capacity utilization. It is therefore also a need to increase the robustness of the services. This calls for increased precision of both the planning and the operation, which can be achieved with a higher degree of automation.

    The research in this thesis is aimed at improving the robustness of railway timetables by combining micro-simulation with mathematical optimization, two methods that today are used frequently by practitioners and researchers but rarely in combination. In this research a sequential approach based on simulating a given timetable and re-optimizing it to reduce the weighted sum of scheduled travel time and predicted average delay is proposed. The approach has generated promising results in simulation studies, in which it has been possible to substantially improve the punctuality and reduce the average delays by only increasing the advertised travel times slightly. Further, the results have also indicated a positive socio-economic benefit. This demonstrates the methods potential usefulness and motivates further research.

  • 2.
    Högdahl, Johan
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.
    Delay Prediction with Flexible Train Order in a MILP Simulation-Optimization Approach for Railway Timetabling2019Conference paper (Refereed)
    Abstract [en]

    This paper considers the problem of minimizing travel times and maximizing travel time reliability, which are important socio-economic properties of a railway transport service, for a given set of departures on a double-track line. In this paper travel time reliability is measured as the average delay, and a delay prediction model for MILP timetable optimization is presented. The average delay prediction model takes into consideration time supplements, buffer times and propagation of delays in the railway network and is not restricted to a fixed order of the trains. Validation of the average delay prediction model, and an evaluation of the approach with combined simulation-optimization for improving railway timetables, are conducted by a simulation study on a part of the Swedish Southern Main Line. Results from the simulation study show that the average delays are reduced by up to approximately 40% and that the punctuality is improved by up to approximately 8%.

  • 3.
    Högdahl, Johan
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.
    Bohlin, Markus
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.
    Fröidh, Oskar
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.
    A combined simulation-optimization approach for minimizing travel time and delays in railway timetables2019In: Transportation Research Part B: Methodological, ISSN 0191-2615, E-ISSN 1879-2367, Vol. 126, p. 192-212Article in journal (Refereed)
    Abstract [en]

    Minimal travel time and maximal reliability are two of the most important properties of a railway transportation service. This paper considers the problem of finding a timetable for a given set of departures that minimizes the weighted sum of scheduled travel time and expected delay, thereby capturing these two important socio-economic properties of a timetable. To accurately represent the complex secondary delays in operational railway traffic, an approach combining microscopic simulation and macroscopic timetable optimization is proposed. To predict the expected delay in the macroscopic timetable, a surrogate function is formulated, as well as a subproblem to calibrate the parameters in the model. In a set of computational experiments, the approach increased the socio-economic benefit by 2-5% and improved the punctuality by 8-25%.

  • 4.
    Högdahl, Johan
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.
    Bohlin, Markus
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning. SICS Swedish ICT Västerås AB, Kopparbergsvägen 10, SE-722 13 Västerås, Sweden.
    Fröidh, Oskar
    KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.
    Combining Optimization and Simulation to Improve Railway Timetable Robustness2017Conference paper (Refereed)
    Abstract [en]

    The Train Timetabling Problem (TTP) is the problem of finding the timetable that utilizes the infrastructure as efficient as possible, while satisfying market demands and operational constraints. As reliability is important to passengers it is important that timetables are robust. In this paper we propose a method that combines optimization and simulation to find the timetable that minimizes the travel times and maximizes the expected punctuality. The core method consists of iteratively re-optimizing a bi-objective mixed integer sequencing timetable model, where both planned travel time and simulated delays are taken into account. Each generated timetable is validated and re-evaluated using the micro-simulation tool RailSys. The advantage of the method is that it captures both the uncertainty of a timetable at the planning stage and the validity of the generated timetable. The method is evaluated on a unidirectional track section of the Western Main Line in Sweden and shows promising results for future research.

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