TIMETABLE MANAGEMENT TECHNIQUE IN RAILWAY CAPACITY ANALYSIS: DEVELOPMENT OF THE HYBRID OPTIMIZATION OF TRAIN SCHEDULES (HOTS) MODEL

There are two general approaches to improve the capacity in a rail corridor, either by applying new capital infrastructure investment or by improving the operation of the rail services. Techniques to evaluate the railway operation include modeling and optimization through the use of commercial timetable management and rail simulation tools. However, only a few of the existing tools include complete features of timetable management techniques (e.g. timetable compression) are equipped with an optimization model for rescheduling and timetable improvement and this is especially true when it comes to the U.S. rail environment that prevalently uses unstructured operation practices. This dissertation explores an application of timetable (TT) management techniques (e.g. rescheduling and timetable compression techniques) in the U.S. rail environment and their effect on capacity utilization and level of service (LOS) parameters. There are many tools and simulation packages used for capacity analysis, by both European and the U.S. rail industry, but due to the differences in the operating philosophy and network characteristics of these two rail systems, European studies tend to use timetable-based simulation tools (e.g. RailSys, OpenTrack) while the non-timetable based tools (e.g. RTC) are commonly used in the U.S. (Chapter 1). This research study investigated potential benefits of using a “Hybrid Simulation” approach that would combine the advantages of both the U.S. and European tools. Two case studies (a single track and a multiple-track case study) were developed to test the hybrid simulation approach, and it was concluded that applying timetable management techniques (e.g. timetable compression technique) is promising when implemented in a single track corridor (Chapter 2), but it is only applicable for the multiple track corridors under directional operation pattern (Chapter 3). To address this, a new heuristic rescheduling and rerouting technique was developed as part of the research to convert a multiple track case study from non-directional operation pattern to a fully directional operation pattern (Chapter 4). The knowledge and skills of existing software, obtained during the development and testing of “Hybrid Simulation”, was used to develop an analytical rescheduling/optimization model called “Hybrid Optimization of Train Schedules” (HOTS) (Chapter 5). While the results of the “Hybrid simulation approach” are promising, the method was also time consuming and challenging, as all respective details and database of the given corridors had to be replicated in both simulation tools. The “HOTS Model” could provide the same functions and features of train rescheduling, but with much less efforts and challenges as in the hybrid simulation. The HOTS model works in conjunction with any commercial rail simulation software and it can reschedule an initial timetable (with or without conflict) to provide a “Conflict-Free” timetable based on user-defined criteria. The model is applicable to various types of rail operations, including single, double and multiple-track corridors, under both directional and nondirectional operation patterns. The capabilities of the HOTS model were tested for the two case studies developed in the research, and its outcomes were compared to those obtained from the commercial software. It was concluded that the HOTS model performed satisfactorily in each of the test scenarios and the model results either improved or maintained the initial timetable characteristics. The results are promising for the future development of the model, but limitations in the current model structure, such as station capacity limits, should be addressed to improve the potential of applying the model for industrial applications

Railroad capacity tools and methodologies in the U.S. and Europe

© 2015, The Author(s). A growing demand for passenger and freight transportation, combined with limited capital to expand the United States (U.S.) rail infrastructure, is creating pressure for a more efficient use of the current line capacity. This is further exacerbated by the fact that most passenger rail services operate on corridors that are shared with freight traffic. A capacity analysis is one alternative to address the situation and there are various approaches, tools, and methodologies available for application. As the U.S. continues to develop higher speed passenger services with similar characteristics to those in European shared-use lines, understanding the common methods and tools used on both continents grows in relevance. There has not as yet been a detailed investigation as to how each continent approaches capacity analysis, and whether any benefits could be gained from cross-pollination. This paper utilizes more than 50 past capacity studies from the U.S. and Europe to describe the different railroad capacity definitions and approaches, and then categorizes them, based on each approach. The capacity methods are commonly divided into analytical and simulation methods, but this paper also introduces a third, “combined simulation–analytical” category. The paper concludes that European rail studies are more unified in terms of capacity, concepts, and techniques, while the U.S. studies represent a greater variation in methods, tools, and objectives. The majority of studies on both continents use either simulation or a combined simulation–analytical approach. However, due to the significant differences between operating philosophy and network characteristics of these two rail systems, European studies tend to use timetable-based simulation tools as opposed to the non-timetable-based tools commonly used in the U.S. rail networks. It was also found that validation of studies against actual operations was not typically completed or was limited to comparisons with a base model

Development of hybrid optimization of train schedules model for N-track rail corridors

© 2016 Elsevier Ltd. From a capacity perspective, efficient utilization of a railway corridor has two main objectives; avoidance of schedule conflicts, and finding a proper balance between capacity utilization and level of service (LOS). There are several timetable tools and commercial rail simulation packages available to assist in reaching these objectives, but few of them offer both automatic train conflict resolution and automatic timetable management features for the different types of corridor configurations. This research presents a new rescheduling model to address some of the current limitations. The multi-objective linear programming (LP) model is called Hybrid Optimization of Train Schedules (HOTS), and it works together with commercial rail simulation tools to improve capacity utilization or LOS metrics. The HOTS model uses both conflict resolution and timetable compression techniques and is applicable to single-, double-, and multiple-track corridors (N-track networks), using both directional and bi-directional operations. This paper presents the approach, formulation and data requirements for the HOTS model. Single and multi-track case studies test and demonstrate the model\u27s train conflict resolution and timetable compression capabilities, and the model\u27s results are validated by using RailSys simulation package. The HOTS model performs well in each tested scenario, providing comparable results (either improved or similar) to the commercial packages

Track maintenance scheduling and its interactions with operations: Dedicated and mixed high-speed rail (HSR) scenarios

HSRs are a complex system not only in terms of technical specifications, but also with respect to operations and maintenance over the track structure. Also, track structure is basically considered as the most important and costly railway asset. Its maintenance is vital to assure safety and operating practices are also of great importance to assure that a good level of service is provided. Considering track maintenance considerations over a new HSR line, one important and critical feature is the operational regime and the question of whether the line will be operated as mixed (passenger and freight) or dedicated only to passenger traffic. This can influence the maintenance patterns: preventive maintenance planning, maintenances scheduling and assignment issues. This will be different for the dedicated and mixed HSR traffic scenarios. In this research, the main approach is focused on the interactions between track maintenance planning and operational concerns and influences in these two scenarios. With this aim and within the current paper, a model of the preventive maintenance scheduling problem (PMSP) has been selected initially from Budai (2006) and then an upgraded revision of this model (Multi-segment assignment and scheduling of preventive maintenance problem) is introduced. Furthermore, the upgraded model of PMSP has been run over a given HSR line (Tehran-Qom HSR corridor in Iran) based on the comparison between the two scenarios of dedicated HSR and upgraded mixed HSR patterns. The main requirements, similarities and differences between these two scenarios are analyzed based on preventive maintenance scheduling and assignment requisites and interactions over the operating restrictions and considerations such as track possession patterns for maintenance activities. We conclude that decision making between these two scenarios through PMSP modeling are quite complicated and depends on the technical and operational specifications of the given HSR corridor, although some general comments on tradeoffs are possible

Analyzing log and chip truck performances in the Upper Peninsula of Michigan with GPS tracking devices

14 p.Rising fuel costs are expected to increase truck rates by 10 to 30 percent over the next two years. Many of the products shipped in this region are heavy, bulk, and raw materials such as logs that benefit from economies of scale and bulk modes of transportation. Current estimates suggest that truck log delivery systems in the region may be operating at less than 50% loaded capacity. The "empty miles" impact not only increases in truck rates but also contributes to needless production of green house gases and carbon emissions. The optimization of truck, rail and marine modes with an efficient intermodal linkage would result in the reduction of transportation costs, congestion, pavement and roadway degradation, and harmful air emissions. This is a preliminary investigation into the potential of optimizing log truck operations and establishing regional log superyards