Designing Rapid Transit Network Design with Alternative routes

The aim of this paper is to propose a model for the design of a robust rapid transit network. In this paper, a network is said to be robust when the effect of disruption on total trip coverage is minimized. The proposed model is constrained by three different kinds of flow conditions. These constraints will yield a network that provides several alternative routes for given origin–destination pairs, therefore increasing robustness. The paper includes computational experiments which show how the introduction of robustness influences network design

Robust rolling stock in rapid transit network

This paper focuses on the railway rolling stock circulation problem in rapid transit networks, in which frequencies are high and distances are relatively short. Although the distances are not very large, service times are high due to the large number of intermediate stops required to allow proper passenger flow. The main complicating issue is the fact that the available capacity at depot stations is very low, and both capacity and rolling stock are shared between different train lines. This forces the introduction of empty train movements and rotation maneuvers, to ensure sufficient station capacity and rolling stock availability. However, these shunting operations may sometimes be difficult to perform and can easily malfunction, causing localized incidents that could propagate throughout the entire network due to cascading effects. This type of operation will be penalized with the goal of selectively avoiding them and ameliorating their high malfunction probabilities. Critic trains, defined as train services that come through stations that have a large number of passengers arriving at the platform during rush hours, are also introduced. We illustrate our model using computational experiments drawn from RENFE (the main Spanish operator of suburban passenger trains) in Madrid, Spain. The results of the model, achieved in approximately 1 min, have been received positively by RENFE planners

Robust rolling stock under uncertain demand in rapid transit networks

This paper focuses on the railway rolling stock circulation problem in rapid transit networks where the known demand and train schedule must be met by a given fleet. In rapid transit networks the frequencies are high and distances are relatively short. Although the distances are not very large, service times are high due to the large number of intermediate stops required to allow proper passenger flow. The previous circumstances and the reduced capacity of the depot stations and that the rolling stock is shared between the different lines, force the introduction of empty trains and a careful control on shunting operation. In practice the future demand is generally unknown and the decisions must be based on uncertain forecast. We have developed a stochastic rolling stock formulation of the problem. The computational experiments were developed using a commercial line of the Madrid suburban rail network operated by RENFE (The main Spanish operator of suburban trains of passengers). Comparing the results obtained by deterministic scenarios and stochastic approach some useful conclusions may be obtained.

Recovery of Disruptions in Rapid Transit Networks

This paper studies the disruption management problem of rapid transit rail networks. Besides optimizing the timetable and the rolling stock schedules, we explicitly deal with the effects of the disruption on the passenger demand. We propose a two-step approach that combines an integrated optimization model (for the timetable and rolling stock) with a model for the passengers’ behavior. We report our computational tests on realistic problem instances of the Spanish rail operator RENFE. The proposed approach is able to find solutions with a very good balance between various managerial goals within a few minutes. Se estudia la gestión de las incidencias en redes de metro y cercanías. Se optimizan los horarios y la asignación del material rodante, teniendo en cuenta el comportamiento de los pasajeros. Se reallizan pruebas en varias líneas de la red de cercanías de Madrid, con resultados satisfactorios.

Railway Rapid Transit timetables with variable and elastic demand.

This paper focuses on the design of railway timetables considering a variable elastic demand profile along a whole design day. Timetabling is the third stage in the classical hierarchical railway planning process. Most of previous works on this topic consider a uniform demand behavior for short planning intervals. In this paper, we propose a MINLP model for designing non-periodic timetables on a railway corridor where demand is dependent on waiting times. In the elastic demand case, long waiting times lead to a loss of passengers, who may select an alternative transportation mode. The mode choice is modeled using two alternative methods. The first one is based on a sigmoid function and can be used in case of absence of information for competitor modes. In the second one, the mode choice probability is obtained using a Logit model that explicitly considers the existence of a main alternative mode. With the purpose of obtaining optimal departure times, in both cases, a minimization of the loss of passengers is used as objective function. Finally, as illustration, the timetabling MINLP model with both mode choice methods is applied to a real case and computational results are shown.