A Local Search Algorithm for Train Unit Shunting with Service Scheduling

In this paper we consider the train unit shunting problem extended with service task scheduling. This problem originates from Dutch Railways, which is the main railway operator in the Netherlands. Its urgency stems from the upcoming expansion of the rolling stock fleet needed to handle the ever-increasing number of passengers. The problem consists of matching train units arriving on a shunting yard to departing trains, scheduling service tasks such as cleaning and maintenance on the available resources, and parking the trains on the available tracks such that the shunting yard can operate conflict-free. These different aspects lead to a computationally extremely difficult problem, which combines several well-known NP-hard problems. In this paper, we present the first solution method covering all aspects of the shunting and scheduling problem. We describe a partial order schedule representation that captures the full problem, and we present a local search algorithm that utilizes the partial ordering. The proposed solution method is compared with an existing mixed integer linear program in a computational study on realistic instances provided by Dutch Railways. We show that our local search algorithm is the first method to solve real-world problem instances of the complete shunting and scheduling problem. It even outperforms current algorithms when the train unit shunting problem is considered in isolation, that is, without service tasks. Although our method was developed for the case of the Dutch Railways, it is applicable to any shunting yard or service location, irrespective of its layout, that uses self-propelling train units and that does not have to handle passing trains.

The Application of Tree-Based Algorithms on Classifying Shunting Yard Departure Status

Shunting yards are one of the main areas impacting the reliability of rail freight networks, and delayed departures from shunting yards can further also affect the punctuality of mixed-traffic networks. Methods for automatic detection of departures, which are likely to be delayed, can therefore contribute towards increasing the reliability and punctuality of both freight and passenger services. In this paper, we compare the performance of tree-based methods (decision trees and random forests), which have been highly successful in a wide range of generic applications, in classifying the status of (delayed, early, and on-time) departing trains from shunting yards, focusing on the delayed departures as the minority class. We use a total number of 6,243 train connections (representing over 21,000 individual wagon connections) for a one-month period from the Hallsberg yard in Sweden, which is the largest shunting yard in Scandinavia. Considering our dataset, our results show a slight difference between the application of decision trees and random forests in detecting delayed departures as the minority class. To remedy this, enhanced sampling for minority classes is applied by the synthetic minority oversampling technique (SMOTE) to improve detecting and assigning delayed departures. Applying SMOTE improved the sensitivity, precision, and F-measure of delayed departures by 20% for decision trees and by 30% for random forests. Overall, random forests show a relative better performance in detecting all three departure classes before and after applying SMOTE. Although the preliminary results presented in this paper are encouraging, future studies are needed to investigate the computational performance of tree-based algorithms using larger datasets and considering additional predictors.

Przydatność kryteriów litogenetycznych w konstrukcji numerycznego modelu krążenia wód podziemnych w strefie krawędziowej wysoczyzny

The aim of the study was to assess the quality of soils underneath operating railway lines. The lines selected for the examination were outside the reach of external sources of potential pollution. The samples were collected along a plain line section after and before an upgrade work, within the station area and in a railway equipment repair yard. The assessment covered the following types of sections: single-track, double-track, with wooden and concrete sleepers, adjacent to switches subject to lubrication, in the car shunting yard and visibly contaminated areas. The samples were tested for the content of PAH, zinc, copper, lead and PCB. The study did not find evidence of increased levels of the above-listed compounds as compared to the levels found in arable soils located in the vicinity of the line or of their influence on adjacent lands. The content of the examined compounds did not differ depending on the type of line section or its properties. The content of PAH, considered one of the main railway-related pollutants, was sufficiently low to classify the soil along the line and within the station area as unpolluted or slightly polluted.

Analiza wybranych parametrów chemicznych gleb wzdłuż linii kolejowych

The aim of the study was to assess the quality of soils underneath operating railway lines. The lines selected for the examination were outside the reach of external sources of potential pollution. The samples were collected along a plain line section after and before an upgrade work, within the station area and in a railway equipment repair yard. The assessment covered the following types of sections: single-track, double-track, with wooden and concrete sleepers, adjacent to switches subject to lubrication, in the car shunting yard and visibly contaminated areas. The samples were tested for the content of PAH, zinc, copper, lead and PCB. The study did not find evidence of increased levels of the above-listed compounds as compared to the levels found in arable soils located in the vicinity of the line or of their influence on adjacent lands. The content of the examined compounds did not differ depending on the type of line section or its properties. The content of PAH, considered one of the main railway-related pollutants, was sufficiently low to classify the soil along the line and within the station area as unpolluted or slightly polluted.