Railway Crew Rescheduling with Retiming

Railway operations are disrupted frequently, e.g. the Dutch railway network experiences about three large disruptions per day on average. In such a disrupted situation railway operators need to quickly adjust their resource schedules. Nowadays, the timetable, the rolling stock and the crew schedule are recovered in a sequential way. In this paper, we model and solve the crew rescheduling problem with retiming. This problem extends the crew rescheduling problem by the possibility to delay the departure of some trains. In this way we partly integrate timetable adjustment and crew rescheduling. The algorithm is based on column generation techniques combined with Lagrangian heuristics. In order to prevent a large increase in computational time, retiming is allowed only for a limited number of trains where it seems very promising. Computational experiments with real-life disruption data show that, compared to the classical approach, it is possible to find better solutions by using crew rescheduling with retiming.

Evaluating the Applicability of Advanced Techniques for Practical Real-time Train Scheduling

AbstractThis paper reports on the practical applicability of published techniques for real-time train scheduling. The final goal is the development of an advanced decision support system for supporting dispatchers’ work and for guiding them toward near-optimal real-time re-timing, re-ordering and re-routing decisions. The paper focuses on the optimization system AGLIBRARY that manages trains at the microscopic level of block sections and block signals and at a precision of seconds. The system outcome is a detailed conflict-free train schedule, being able to avoid deadlocks and to minimize train delays. Experiments on a British railway nearby London demonstrate that AGLIBRARY can quickly compute near-optimal solutions

Train scheduling with application to the UK rail network

Nowadays, transforming the railway industry for better performance and making the best usage of the current capacity are the key issues in many countries. Operational research methods and in particular scheduling techniques have a substantial potential to offer algorithmic solutions to improve railway operation and control. This thesis looks at train scheduling and rescheduling problems in a microscopic level with regard to the track topology. All of the timetable components are fixed and we aim to minimize delay by considering a tardiness objective function and only allowing changes to the order and to the starting times of trains on blocks. Various operational and safety constraints should be considered. We have achieved further developments in the field including generalizations to the existing models in order to obtain a generic model that includes important additional constraints. We make use of the analogy between the train scheduling problem and job shop scheduling problem. The model is customized to the UK railway network and signaling system. Introduced solution methods are inspired by the successful results of the shifting bottleneck to solve the job shop scheduling problems. Several solution methods such as mathematical programming and different variants of the shifting bottleneck are investigated. The proposed methods are implemented on a real-world case study based on London Bridge area in the South East of the UK. It is a dense network of interconnected lines and complicated with regard to stations and junctions structure. Computational experiments show the efficiency and limitations of the mathematical programming model and one variant of the proposed shifting bottleneck algorithms. This study also addresses train routing and rerouting problems in a mesoscopic level regarding relaxing some of the detailed constraints. The aim is to make the best usage of routing options in the network to minimize delay propagation. In addition to train routes, train entry times and orders on track segment are defined. Hence, the routing and scheduling decisions are combined in the solutions arising from this problem. Train routing and rerouting problems are formulated as modified job shop problems to include the main safety and operational constraints. Novel shifting bottleneck algorithms are provided to solve the problem. Computational results are reported on the same case study based on London Bridge area and the results show the efficiency of one variant of the developed shifting bottleneck algorithms in terms of solution quality and runtime

Simulation and Control of Groups of People in Multi-modal Mobility

Tourism and transport are constantly growing and, with it, the movements of travellers. This entails two fundamental effects on which we must focus: control of mass tourism and the organization of transport. Good transport organization and travel planning avoid crowds and therefore mass tourism. This allows promoting sustainable tourism in which it is sought to offer a quality service to tourists taking care of the environment. In this thesis the objective is to manage the flow of groups of people through means of transport. This control of groups of people is aimed at customer satisfaction by offering quality tourism. On the one hand, the study focuses on the problem to mitigate the negative effects due to mass arrivals in touristic locations. A TEN network has been developed to define the optimal tours for different groups of tourists. A related mixed integer quadratic optimization model has been developed with three main objectives: it minimizes the maximum value of occupancy in the selected destinations to limit mass tourism, reduces the divergence between the proposed visit tour and one required by the tourist group and the overall duration of their visit, and a heuristic approach has been introduced. On the other hand, it has been implemented a railway scheduling and rescheduling problem introducing optimization-based and min-max approaches on the regional and high-speed railway network. The scheduling model defines the best schedules for a set of trains considering costumers\u2019 demand and the priority of the trains to cover the rail sections in case of conflict on the railway lines. Consecutively, the generated feasible timetables are used to minimize possible consequences due to events that may negatively affect the real time traffic management. The main contribution of this section is the introduction in the second approach the innovative concept to prioritize the train that can access on the block section in case of conflicts on the network

Design of a final approach spacing tool for TRACON air traffic control

This paper describes an automation tool that assists air traffic controllers in the Terminal Radar Approach Control (TRACON) Facilities in providing safe and efficient sequencing and spacing of arrival traffic. The automation tool, referred to as the Final Approach Spacing Tool (FAST), allows the controller to interactively choose various levels of automation and advisory information ranging from predicted time errors to speed and heading advisories for controlling time error. FAST also uses a timeline to display current scheduling and sequencing information for all aircraft in the TRACON airspace. FAST combines accurate predictive algorithms and state-of-the-art mouse and graphical interface technology to present advisory information to the controller. Furthermore, FAST exchanges various types of traffic information and communicates with automation tools being developed for the Air Route Traffic Control Center. Thus it is part of an integrated traffic management system for arrival traffic at major terminal areas

The Center/TRACON Automation System (CTAS): A video presentation

NASA Ames, working with the FAA, has developed a highly effective set of automation tools for aiding the air traffic controller in traffic management within the terminal area. To effectively demonstrate these tools, the video AAV-1372, entitled 'Center/TRACON Automation System,' was produced. The script to the video is provided along with instructions for its acquisition