Dispatching and Rescheduling Tasks and Their Interactions with Travel Demand and the Energy Domain: Models and Algorithms

Abstract The paper aims to provide an overview of the key factors to consider when performing reliable modelling of rail services. Given our underlying belief that to build a robust simulation environment a rail service cannot be considered an isolated system, also the connected systems, which influence and, in turn, are influenced by such services, must be properly modelled. For this purpose, an extensive overview of the rail simulation and optimisation models proposed in the literature is first provided. Rail simulation models are classified according to the level of detail implemented (microscopic, mesoscopic and macroscopic), the variables involved (deterministic and stochastic) and the processing techniques adopted (synchronous and asynchronous). By contrast, within rail optimisation models, both planning (timetabling) and management (rescheduling) phases are discussed. The main issues concerning the interaction of rail services with travel demand flows and the energy domain are also described. Finally, in an attempt to provide a comprehensive framework an overview of the main metaheuristic resolution techniques used in the planning and management phases is shown

Optimization in railway timetabling for regional and intercity trains in Zealand: A case of study of DSB

The Train Timetabling Problem is one of the main tactical problems in the railway planning process. Depending on the size of the network, the problem can be hard to solve directly and alternative methods should be studied. In this thesis, the Train Timetabling Problem is formulated using a graph formu-lation that takes advantage of the symmetric timetabling strategy and assumed fixed running times between station. The problem is formulated for the morning rush hour period of the Regional and InterCity train network of Zealand. The solution method implemented is based on a Large Neighborhood Search model that iteratively applies a dive-and-cut-and-price procedure. An LP relax version of the problem is solved using Column Generation considering only a subset of columns and constraints. Each column corresponds to the train paths of a line that are found by shortest paths in the graphs. Then, violated constraints are added by separation and an heuristic process is applied to help finding integer solutions. Last, the passengers are routed on the network based on the found timetable and the passenger travel time calculated. The process is repeated taking into account the best transfers from the solution found. A parameter tuning is conducted to find the best algorithm setting. Then, the model is solved for different scenarios where the robustness and quality of the solution is analyzed. The model shows good performance in most of the scenarios being able to find good quality solutions relatively fast. The way the best transfers are considered between timetable solutions does not add significant value in terms of solution quality but could be useful from a planning perspective. In addition, most of the real-life conflicts are taken into account in the model but not all of them. As a result, the model can still be improved in order to provide completely conflict-free timetables. In general, the model appears to be useful for the timetabling planning process of DSB. It allows to test different network requirements and preferences easily. The model not only generates a timetable but also estimates the passenger travel time and the occupancy of the trains quite accurately. Also, any modification in the line plan can easily be included without affecting the core model.Outgoin

Value chain management as a strategy to achieve competitive advantage in the railway industry: a case study of Swaziland Railway.

Master’s degree. University of KwaZulu-Natal, Durban.The concept of value chain management for competitive advantage is not new in the railway business. However, competition from other modes of transport such as road transportation, has created fierce competition, and as a result some railway companies are still finding it difficult to be sustainable in the industry. The aim of this study was to examine how the value chain systems in the railway sector could be integrated in an organisation mainframe, to gain and maintain competitive advantage within the railway transport sector – using the case of Swaziland Railway (SR). This study adopted a descriptive quantitative research design using the population size of all the managers and technical supervisors at SR. This cohort group was involved in the designing and implementation of a value chain management strategy for the company. A random sampling technique was used and the sample size was forty five (45) employees. Data were collected using a questionnaire and were analysed through a descriptive data analysis technique which projected the findings on a histogram, in terms of frequencies. The findings of the study indicate that most employees (56%) showed a positive response – indicating that technology, train efficiency and rail infrastructure had an impact on the company’s value chain management system. The main recommendation of the study is continuous improvements through engagement of other efficiency-driven service delivery technologies. Introduction of sophisticated electronic measures in respect of the safety and security of customer cargo, and improvements in the adequacy of rolling stock in order to increase capacity, efficiency and effectiveness. Improve safety and reliability of the rail network infrastructure to meet customer demands, provide cost effective and efficient service

Designing robust schedule coordination scheme for transit networks with safety control margins

We propose a robust schedule coordination scheme which combines timetable planning with a semi-flexible departure delayed control strategy in case of disruptions. The flexibility is provided by allowing holding for the late incoming bus within a safety control margin (SCM). In this way, the stochastic travel time is addressed by the integration of real-time control and slacks at the planning phase. The schedule coordination problem then jointly optimises the planning headways and slack times in the timetable subject to SCM. Analytical formulations of cost functions are derived for three types of operating modes: uncoordinated operation, departure punctual control and departure delayed control. The problem is formulated as a stochastic mixed integer programming model and solved by a branch-and-bound algorithm. Numerical results provide an insight into the interaction between SCM and slack times, and demonstrate that the proposed model leads to cost saving and higher efficiency when SCM is considered. Compared to the conventional operating modes, the proposed method also presents advantages in transfer reliability and robustness to delay and demand variation

How do principles for human-centred automation apply to Disruption Management Decision Support?

While automation of signal and route setting is routine, the use of automation or decision support in disruption management processes is far less common. Such support offers significant advantages in optimising re-planning of both timetable and resources (crew and rolling stock), and has value in offering a 'shared view' of re-planning across the many actors manage disruption. If this vision is to be realised, however, disruption management decision support and automation must adhere to proven principles for effective human-agent cooperation. This paper synthesises data from a programme of work to understand user requirements for automated disruption support tools. It then compares these outputs with two frameworks for human-centred automation - one general (Klein et al's [2004] ten challenges for automation) and one transport specific (Balfe et al’s [2012] principles for transport automation). Emergent design requirements include the need for iterative modification of rescheduling parameters throughout a disruption, visibility of the reasoning behind options, accountability remaining in the hands of disruption controllers, and the need for the automated disruption support tools to take a multi-dimensional view of disruption that varies depending on the event encountered. The paper reflects on the practical utility of high-level design principles for automated disruption support tools