Heuristics for railway infrastructure saturation

AbstractThis research concerns the problem of the evaluation of the railway infrastructure capacity. It is an important question when railway authorities have to choose between different infrastructure investment projects. We developped independently two heuristic approaches to solve the infrastructure saturation problem. The first is based on a constraint programming model which is solved using a greedy heuristic. The second approach identifies the saturation problem as a unicost set packing problem and its resolution is ensured by an adaption of GRASP metaheuristic. Currently, both resolution techniques are not in competition. The goal is to grasp the resolution ability of the heuristics and to analyse the kind of solutions produced. The Pierrefitte-Gonesse junction has been used as experimental support. A software environment allows to simulate several timetables involving TGV, Inter City and Freight trains

Railway freight node capacity evaluation: A timetable-saturation approach and its application to the Novara freight terminal

Abstract This paper presents a timetable-based approach to assess the capacity of a railway freight node, based on the microscopic simulation and saturation of the timetable. Saturation is done by scheduling additional saturation train paths without introducing any traffic conflict, while respecting the required technical and operational constraints, until no more paths can be added. The approach is applied to analyze the potential effects on capacity of some infrastructure improvements planned by Rete Ferroviaria Italiana (RFI) for the rail freight node of Novara, Italy. The capacity is evaluated by means of two KPIs computed on saturated timetables: the number of daily pairs of saturation freight trains and the infrastructure Occupancy Time Rate (OTR). The first KPI represents an absolute estimation of the capacity (theoretical or practical, depending on the presence of buffer times). Instead, the OTR is computed by the UIC 406R compression method and it is used to identify local bottlenecks. For the analysis, we use SASTRE, an analysis environment for railway systems developed at Politecnico di Torino, which combines a MILP formulation for the timetable saturation problem with a saturation strategy layer. The saturation strategy considers a given set of priorities between the different network areas and the train types to be used during the saturation process. The results reveal that using a microscopic model to schedule traffic flows on a complex railway node allows for a good accuracy of the timetable, but at a high computational cost

A Study on the Practical Carrying Capacity of Large High-Speed Railway Stations considering Train Set Utilization

Methods for solving the carrying capacity problem for High-Speed Railways (HSRs) have received increasing attention in the literature in the last few years. As important nodes in the High-Speed Railway (HSR) network, large stations are usually the carrying capacity bottlenecks of the entire network due to the presence of multiple connections in different directions and the complexity of train operations at these stations. This paper focuses on solving the station carrying capacity problem and considers train set utilization constraints, which are important influencing factors that have rarely been studied by previous researchers. An integer linear programming model is built, and the CPLEX v12.2 software is used to solve the model. The proposed approach is tested on a real-world case study of the Beijing South Railway Station (BS), which is one of the busiest and most complex stations in China. Studies of the impacts of different train set utilization constraints on the practical station carrying capacity are carried out, and some suggestions are then presented for enhancing the practical carrying capacity. Contrast tests indicate that both the efficiency of the solving process and the quality of the solution show huge breakthroughs compared with the heuristic approach

A Study on the Practical Carrying Capacity of Large High-Speed Railway Stations considering Train Set Utilization

Methods for solving the carrying capacity problem for High-Speed Railways (HSRs) have received increasing attention in the literature in the last few years. As important nodes in the High-Speed Railway (HSR) network, large stations are usually the carrying capacity bottlenecks of the entire network due to the presence of multiple connections in different directions and the complexity of train operations at these stations. This paper focuses on solving the station carrying capacity problem and considers train set utilization constraints, which are important influencing factors that have rarely been studied by previous researchers. An integer linear programming model is built, and the CPLEX v12.2 software is used to solve the model. The proposed approach is tested on a real-world case study of the Beijing South Railway Station (BS), which is one of the busiest and most complex stations in China. Studies of the impacts of different train set utilization constraints on the practical station carrying capacity are carried out, and some suggestions are then presented for enhancing the practical carrying capacity. Contrast tests indicate that both the efficiency of the solving process and the quality of the solution show huge breakthroughs compared with the heuristic approach