In this paper, we review the main concepts and methods to perform capacity analyses, and we present an automated tool that is able to perform several capacity analyses. Capacity is extremely dependent on infrastructure, tra‐c, and operating parameters. Therefore, an in-depth study of the main factors that in∞uence railway capacity is performed on several Spanish railway infrastructures. The results show how the capacity varies according to factors such as train speed, commercial stops, train heterogeneity, distance between railway signals, and timetable robustness. One consequence of the globalization of the economy and the increasing integration of the international economies is a considerable growth in the entire transport sector. During the 1990’s, many countries began to sufier from congestion in certain areas and on certain routes. Nowadays, there is no doubt about the congestion of the transport situation in some countries. The problem is now beginning to threaten economic competitiveness. Greater economic development cannot take place in the current transport scenario unless ambitious measures are taken. Revitalizing the railways is one of the principal measures

/pdf/an-assessment-of-railway-capacity-14qwt0gaps.pdf

An Assessment of Railway Capacity

This paper presents applications of the Transit Capacity and Quality of Service Manual (TCQSM) methodologies to fixed-route transit systems in Mexico. The applications are focused on the quality of service part of the manual. The TCQSM provides a simple and clear way to analyze transit systems in other countries such as Mexico as there are no significant differences with transit systems in the US. However, several factors and thresholds such as walking distance, passenger load factors, transit supportive areas and the difference between transit and auto travel times should be further researched and adapted to local conditions since these values have a significant effect on the determination of the appropriate level-of-service (LOS). Furthermore, there are other performance measures such as on-time reliability, safety and security, and headway adherence that are not commonly reported by transit systems in Mexico and therefore, the TCQSM methodologies are not applicable. The paper describes the applications and the adjustments necessary to apply such methodologies and highlights its advantages and limitations for applications in Mexico.

Transit Capacity and Quality-of-Service Manual: Applications to Mexican Transit Systems

We study the problem of freight transportation in railway networks, where both passenger and freight trains are run. While the passenger trains have a prescribed timetable that cannot be changed, freight train operators send the infrastructure manager requests to insert new freight trains. For each freight train, the associated train operator specifies a preferred ideal timetable , which can be modified by the infrastructure manager in order to respect safeness operational constraints. In particular, this modification may correspond to routing the train along a path which is different with respect to the one in the ideal timetable. Roughly speaking, the objective is to introduce as many new freight trains as possible by assigning them timetables that are as close as possible to the ideal ones. For this timetabling problem on a generic railway network, we present an integer linear programming formulation, that generalizes some formulations already presented for the case of a single railway line, and a Lagrangian heuristic based on this formulation. Computational results on real-world instances are reported.

Scheduling extra freight trains on railway networks

Railway planning is a complex activity which is usually decomposed into several stages, traditionally network design, line design, timetabling, rolling stock, and staffing. In this paper, we study the design and optimization of train timetables for a rail rapid transit (RRT) line adapted to a dynamic demand environment, which focuses on creating convenient timetables for passengers. The objective is to minimize the average passenger waiting time at the stations, thus focusing on passenger welfare. We first propose two mathematical programming formulations which generalize the non-periodic train timetabling problem on a single line under a dynamic demand pattern. We then analyze the properties of the problem before introducing a fast adaptive large neighborhood search (ALNS) metaheuristic in order to solve large instances of the problem within short computation times. The algorithm yields timetables that may not be regular or periodic, but are adjusted to a dynamic demand behavior. Through extensive computational experiments on artificial and real-world based instances, we demonstrate the computational superiority of our ALNS compared with a truncated branch-and-cut algorithm. The average reduction in passenger waiting times is 26%, while the computational time of our metaheuristic is less than 1% of that required by the alternative CPLEX-based algorithm. Out of 120 open instances, we obtain 84 new best known solutions and we reach the optimum on 10 out of 14 instances with known optimal solutions.

https://events.barcelonagse.eu/live/files/636-barrena

Single-line rail rapid transit timetabling under dynamic passenger demand

https://www.cirrelt.ca/DocumentsTravail/CIRRELT-2013-41.pdf

Exact formulations and algorithm for the train timetabling problem with dynamic demand

This work is focused on the application of evolutionary algorithms to solve very complex real-world problems. For this purpose a Genetic Algorithm is designed to solve the Train Timetabling Problem. Optimizing train timetables on a single line track is known to be NP-hard with respect to the number of conflicts in the schedule. This makes it difficult to obtain good solutions to real life problems in a reasonable computational time and raises the need for good heuristic scheduling techniques. The railway scheduling problem considered in this work implies the optimization of trains on a railway line that is occupied (or not) by other trains with fixed timetables. The timetable for the new trains is obtained with a Genetic Algorithm (GA) that includes a guided process to build the initial population. The proposed GA is tested using real instances obtained from the Spanish Manager of Railway Infrastructure (ADIF). The results of the computational experience, point out that GA is an appropriate method to explore the search space of this complex problems and able to lead to good solutions in a short amount of time.

A Genetic Algorithm for Railway Scheduling Problems

http://users.dsic.upv.es/~msalido/papers/EAAI-Abril-Salido-Barber.pdf

Distributed search in railway scheduling problems

Many combinatorial problems can be modelled as Constraint Satisfaction Problems (CSPs). Solving a general CSP is known to be NP-complete, so closure and heuristic search are usually used. However, many problems are inherently distributed and the problem complexity can be reduced by dividing the problem into a set of subproblems. Nevertheless, general distributed techniques are not always appropriate to distribute real-life problems. In this work, we model the railway scheduling problem by means of domain-dependent distributed constraint models, and we show that these models maintained better behaviors than general distributed models based on graph partitioning. The evaluation is focused on the railway scheduling problem, where domain-dependent models carry out a problem distribution by means of trains and contiguous sets of stations.

/pdf/domain-dependent-distributed-models-for-railway-scheduling-26dnktvkyc.pdf

Domain-dependent distributed models for railway scheduling

With the aim of supporting the process of adapting railway infrastructure to present and future traffic needs, we have developed a method to build train timetables efficiently. In this work, we describe the problem in terms of constraints derived from railway infrastructure, user requirements and traffic constraints, and we propose a method to solve it efficiently. This method carries out the search by assigning values to variables in a given order and verifying the satisfaction of constraints where these are involved. When a constraint is not satisfied, a guided backtracking is done. The technique reduces the search space allowing us to solve real and complex problems efficiently.

M. Abril

Papers

An Assessment of Railway Capacity

A Genetic Algorithm for Railway Scheduling Problems

Distributed search in railway scheduling problems

Domain-dependent distributed models for railway scheduling

An Efficient Method to Schedule New Trains on a Heavily Loaded Railway Network