Combinatorial optimization model for railway engine assignment problem

This paper presents an experimental study for the Hungarian State Railway Company (M\'AV). The engine assignment problem was solved at M\'AV by their experts without using any explicit operations research tool. Furthermore, the operations research model was not known at the company. The goal of our project was to introduce and solve an operations research model for the engine assignment problem on real data sets. For the engine assignment problem we are using a combinatorial optimization model. At this stage of research the single type train that is pulled by a single type engine is modeled and solved for real data. There are two regions in Hungary where the methodology described in this paper can be used and M\'AV started to use it regularly. There is a need to generalize the model for multiple type trains and multiple type engines

The Maraca: a tool for minimizing resource conflicts in a non-periodic railway timetable

While mathematical optimization and operations research receive growing attention in the railway sector, computerized timetabling tools that actually make significant use of optimization remain relatively rare. SICS has developed a prototype tool for non-periodic timetabling that minimizes resource conflicts, enabling the user to focus on the strategic decisions. The prototype is called the Maraca and has been used and evaluated during the railway timetabling construction phase at the Swedish Transport Administration between April and September 2010

Route Planning in Transportation Networks

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4, previously published by Microsoft Research. This work was mostly done while the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at Microsoft Research Silicon Valle

Paying Less for Train Connections with MOTIS

Finding cheap train connections for long-distance traffic is algorithmically a hard task due to very complex tariff regulations. Several new tariff options have been developed in recent years, partly to react on the stronger competition with low-cost airline carriers. In such an environment, it becomes more and more important that search engines for travel connections are able to find special offers efficiently. We have developed a multi-objective traffic information system (MOTIS) which finds all attractive train connections with respect to travel time, number of interchanges, and ticket costs. In contrast, most servers for timetable information as well as the theoretical literature on this subject focus only on travel time as the primary objective, and secondary objectives like the number of interchanges are treated only heuristically. The purpose of this paper is to show by means of a case study how several of the most common tariff rules (including special offers) can be embedded into a general multi-objective search tool. Computational results show that a multi-objective search with a mixture of tariff rules can be done almost as fast as just with one regular tariff. For the train schedule of Germany, a query can be answered within 1.9s on average on a standard PC

Influence of Signalling Systems on the Capacity of Railways by Lines and Nodes Assessment Methods

In the complex railway networks characterized by mixed traffic, a key focus is the increase of railway capacity by high performances signalling systems, including ETCS/ERTMS and beyond. Nevertheless, the estimation of effects on headway of the introduction of innovations in signalling systems is complex and not consolidated for complex networks characterized by mixed passenger-freight traffic. This study highlights several challenges on line-node capacity calculation of congested network considering a combined effect of routes conflicts in stations on lines and propagation in station of delays suffered along the lines. The paper describes some results of the ongoing research based on the integrated use of analytical methods and simulation to networks controlled by different standard signaling systems and innovative hybrid solutions able to increase the capacity under specific operational conditions. The paper introduces the application of the methods to the complex mixed-traffic network in Trieste railway node, situated in Northeast of Italy, including the main passengers and freight terminals and the lines operated for both services. The objective is to identify the most appropriate technological solutions and methodological approach for the optimization of the network capacity and minimization of the delays

The Ideal Train Timetabling Problem

The aim of this paper is to analyze and to improve the current planning process of the passenger railway service. At first, the state-of-the-art in research is presented. However, given the recent changes in legislature allowing competitors in the railway industry, the current way of planning is not sufficient anymore. The original planning is based on the accessibility/mobility concept provided by one carrier, whereas the competitive market consists of several carriers that are driven by the profit. Moreover, the current practice does not define the ideal timetables and thus it is assumed that they evolve incrementally, based on a historical data (train occupation, ticket sales, etc.). And thus, we introduce a definition of an ideal timetable that is expressed using the passenger cost. In order to create the timetables itself, we propose to insert the Ideal Train Timetabling Problem (ITTP) that is solved for each Train Operating Company (TOC) separately, into the planning process. The ITTP approach incorporates the passenger demand in the planning and its aim is to minimize the passenger cost(s). The outcome of the ITTP is the ideal timetables (including connections between the trains and weighted by the demand), which then serve as an input for the traditional Train Timetabling Problem (TTP). The TTP takes into account wishes of each TOC (the ideal timetables) and creates global feasible timetable for the given railway network, while minimizing the changes of the TOCs wishes. The ITTP is in line with the new market structure and it can produce both: non-cyclic and cyclic timetables. The model is tested on the data provided by the Israeli Railways (IR). The instance consists of a full demand OD Matrix of an average working day in Israel during 2008. The results are compared to the current timetable of IR. Due to the large complexity of the model, it is solved using the Column Generation methodology